Design and Implementation of an Analog Video Signal Quality Measuring Software for Component Video

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Institutionen för systemteknik

Department of Electrical Engineering

Examensarbete

Design and Implementation of an Analog Video

Signal Quality Measuring Software for Component

Video

Examensarbete utfört i Informationskodning vid Tekniska högskolan i Linköping

av

Carl Ljungström

LITH-ISY-EX--10/4206--SE Linköping 2010

Department of Electrical Engineering Linköpings tekniska högskola

Linköpings universitet Linköpings universitet

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Design and Implementation of an Analog Video

Signal Quality Measuring Software for Component

Video

Examensarbete utfört i Informationskodning

vid Tekniska högskolan i Linköping

av

Carl Ljungström

LITH-ISY-EX--10/4206--SE

Handledare: Andreas Larsson

Motorola AB

Examinator: Robert Forchheimer

isy, Linköpings universitet Linköping, 9 November, 2010

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Avdelning, Institution

Division, Department

Division of Information Coding Department of Electrical Engineering Linköpings universitet

SE-581 83 Linköping, Sweden

Datum Date 2010-11-09 Språk Language ¤ Svenska/Swedish ¤ Engelska/English ¤ £ Rapporttyp Report category ¤ Licentiatavhandling ¤ Examensarbete ¤ C-uppsats ¤ D-uppsats ¤ Övrig rapport ¤ £

URL för elektronisk version

http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-54371

ISBN

—

ISRN

LITH-ISY-EX--10/4206--SE

Serietitel och serienummer

Title of series, numbering

ISSN

—

Titel

Title

Design och implementering av utvärderingsmjukvara för signalkvalitet i analog komponentvideo

Design and Implementation of an Analog Video Signal Quality Measuring Software for Component Video

Författare

Author

Carl Ljungström

Sammanfattning

Abstract

An IP based set-top box (STB) is essentially a lightweight computer used to re-ceive video over the Internet and convert it to analog or digital signals understood by the television. During this transformation from a digital image to an analog video signal many different types of distortions can occur. Some of these distor-tions will affect the image quality in a negative way. If these distordistor-tions could be measured they might be corrected and give the system a better image quality.

This thesis is a continuation of two previous theses where a custom hardware for sampling analog component video signals was created. A software used to com-municate with the sampling hardware and perform several different measurements on the samples collected has been created in this thesis.

The analog video signal quality measurement system has been compared to a similar commercial product and it was found that all except two measurement methods gave very good results. The remaining two measurement methods gave acceptable result. However the differences might be due to differences in imple-mentation. The most important thing for the measurement system is to have consistency. If a system has consistency then any changes leading to worse video quality can be found.

Nyckelord

Keywords set-top box, analog video, signal quality, component video, video quality measure-ment, RGB, YPbPr, subjective measuring

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Abstract

An IP based set-top box (STB) is essentially a lightweight computer used to re-ceive video over the Internet and convert it to analog or digital signals understood by the television. During this transformation from a digital image to an analog video signal many different types of distortions can occur. Some of these distor-tions will affect the image quality in a negative way. If these distordistor-tions could be measured they might be corrected and give the system a better image quality.

This thesis is a continuation of two previous theses where a custom hardware for sampling analog component video signals was created. A software used to com-municate with the sampling hardware and perform several different measurements on the samples collected has been created in this thesis.

The analog video signal quality measurement system has been compared to a similar commercial product and it was found that all except two measurement methods gave very good results. The remaining two measurement methods gave acceptable result. However the differences might be due to differences in imple-mentation. The most important thing for the measurement system is to have consistency. If a system has consistency then any changes leading to worse video quality can be found.

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Acknowledgments

I would like to thank Motorola for giving me the opportunity to do this thesis. A special thanks go to my supervisor Andreas Larsson at Motorola for his valuable support, opinions and suggestions. Another person to thank at the company is Tomas Franzon who helped me with the threads, GUI and other parts of the software.

Two other Motorola thesis writers to thank are Kristofer Gustafsson and Johan Jakobsson that during each lunch break faced me in a good game of Foosball.

A big thanks go to my family for all the help during my whole education, especially my mother and father but also my brothers.

I would also like to thank my girlfriend Emilie Toresson for her support during the whole thesis. Without you this thesis would not be what it is.

A final thanks go to my examiner Robert Forchheimer and my opponent Gustaf Johansson.

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9.3.3 Time . . . 65 10 Conclusion 67 10.1 Results . . . 67 10.2 Subjective measurements . . . 67 10.3 Performance . . . 68 10.4 Scalability . . . 68 10.5 Further work . . . 68 10.5.1 Measurement methods . . . 68 10.5.2 GUI . . . 68 10.5.3 Measurement reports . . . 69 10.6 Final thoughts . . . 69 Bibliography 71 A Glossary 75

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List of Figures

2.1 Image created in a CRT by scanning across the screen in lines. . . 7

2.2 A typical video signal line with sync, front and back porch, color burst and video data. . . 11

2.3 NTSC signal with vertical and horizontal sync signals [Ins07]. . . . 15

2.4 PAL/SECAM signal with vertical and horizontal sync signals [Ins07]. 15 3.1 Two images with the same PSNR value but different distortions. . 19

4.1 Overview of the video sampling system. . . 25

4.2 Overview of the video sampling hardware. . . 26

5.1 An example of a test pattern used for testing distortions. . . 30

6.1 Overview of the software system. . . 42

7.1 Overview implementation parts of the software system. . . 44

7.2 Two different types of line extractions. . . 48

8.1 Main window of MOViA. . . 57

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List of Tables

7.1 Relation between measurement methods and the distortion types. . 48

9.1 Comparison between MOViA and VM6000 for 576i signal . . . 62

9.2 Comparison between MOViA and VM6000 for 720p signal . . . 62

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Chapter

1

Introduction

1.1 Background

An IP based set-top box (STB) is a unit used to receive TV through the Internet. It is essentially a small computer used to convert the digital video and data signals from the Internet and convert them to analog or digital signals understood by the TV. At the moment the market for STB is very strong and is expected to continue to grow [Wir08].

In the never ending quest for perfect image quality, higher and higher resolu-tions are used in modern TV’s. As a result the need for higher resoluresolu-tions from the STB is also needed. But what good is resolution if the picture is distorted in some way?

To ensure that the highest quality is produced and maintained one possible way is to measure the image quality produced by the STB. The image quality from an analog video signal is affected by the signal quality and therefore this could instead be measured. There are a few products available on the market for analog video signal measurements, but the price is high and the flexibility of these units are low.

This thesis is a continuation of two previous theses where a custom hardware for sampling of analog signals was constructed. This hardware system consists of an FPGA which can sample four channels into a memory. The information is then transmitted to a specially designed software in a computer.

The final product of this thesis is to be used internally at Motorola in Linköping for evaluating the video quality of STB’s.

1.2 Purpose

The purpose of this thesis is to develop a software for analyzing signal quality of component video signals (YPbPr and RGB) from an STB. The software should

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use the custom hardware to sample analog video signals and analyze with several different methods.

• What measurements should be chosen in order to ensure good quality?

• Could subjective measurements be used instead of objective measurements?

• How should the chosen measurement methods be implemented in software?

• How should a GUI be created for maximum efficiency?

1.3 Delimitations

The final product of this thesis is only to be used internally at Motorola, as de-scribed earlier, and therefore some limitations are made to fit their requirements. All measurements are made on the analog outputs of the STB and the only thing this thesis will focus on is the conversion from digital signals to analog signals in a STB. All degradations in the image as a result of transmission errors, video decoding and such are not investigated. However these degradations in the image might affect the video signal and might also affect the measurement result. Only component formats, RGB and YPbPr, will be analyzed since a measurement unit for analyzing composite signals is already available. The investigation into subjec-tive measurements will only be on a theoretical level and no implementation will be made.

1.4 Method

This thesis is based on literature but the main part is an empirical investigation since very little literature is available on this type of products. The investigation is performed as an iterative development process but when it comes to the devel-opment of the measurement methods there are a few steps needed for each of the iterations.

The first step is to find as much information available as possible about the distortions to be measured. Where and when do they occur in the picture? What image pattern is needed to recreate the distortions in order to measure them? Some types of distortions are already well known and documented so for those this step might not be needed.

When it is fully understood where and when the distortion occurs the next step is to simulate this. A method is then created to find and measure the distortions. All this work is performed in Matlab [Mat] since many functions needed for the measurements are already available. This phase may need some iterations until the best method is created.

The next part is to implement the function in the final product. This should now be very straightforward after all the testing. However some extra work will be needed since some functions in Matlab are available from start and these needs to be recreated in the new software.

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1.5 Document overview 5

Finally the last step is to test the product with real data and compare with a commercial measurement product to ensure that it measures the distortions correctly.

1.5 Document overview

Chapter 1 gives a short introduction and specifies the objectives of this thesis.

Chapter 2 is an introduction into how analog video signals are created and the different types of signals.

Chapter 3 provides an evaluation of subjective measuring methods to see if these could be used instead of the normal objective methods for video quality measurements.

Chapter 4 describes the sampling system and how each part connects and com-municates.

Chapter 5 breaks down the problem to several different types of distortions that are interesting to measure. This chapter also contains a list of requirements on the sampling system.

Chapter 6 presents the overall design of the software used to collect and measure video signals.

Chapter 7 describes how the design is used to create an implementation of the software.

Chapter 8 describes how the GUI was designed and implemented.

Chapter 9 contains an evaluation of the finished system.

Chapter 10 provides a final conclusion and discusses where further work can be performed.

1.6 Reading instructions

Depending on the background of the reader a few chapters might be skipped if adequate knowledge exists about analog video systems.

• Chapter 2 will give a short introduction into analog video systems needed to understand the rest of the thesis.

• If subjective measurements interest the reader, chapter 3 will give a short introduction and provide the current status of the field.

• For those only interested in how the system was designed and implemented chapter 6 will provide a good start.

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1.7 Glossary

Each of the abbreviations are described the first time they are used but for a complete list see appendix A.

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Chapter

2

Analog video signal theory

In almost every home today there is a television and there are many different ways available for receiving a video signal. Both analog and digital transmissions are available nowadays, however more and more countries are changing to digital transmission since this offers better image and higher resolutions [Sil09]. In the beginning of the television era there were only analog signals available, the screens were monochrome and the audio in mono. Since the monochrome screens only requires a single signal for video and one signal for sound the need for bandwidth is very moderate.

Figure 2.1. Image created in a CRT by scanning across the screen in lines.

The first televisions contained a cathode ray tube, CRT, which is a large vac-uum tube with an electron gun at the back. This electron gun sends out electrons toward the front of the screen where a fluorescent layer is applied. When the elec-trons hit the fluorescent layer a light is produced in that spot. If electro magnets are added in such way that the electron beam can be deflected both horizontally and vertically the beam can reach the whole screen. By moving or scanning the electron beam horizontally across the screen an image is created [Jac01, p. 8]. For an example of the scanning method see figure 2.1.

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The monochromatic screens only contained one electron gun and one type of material on the glass screen. Depending on the amount of electrons hitting the screen the intensity could be changed at any point on the screen. In color screens there are three electron guns and for each pixel on the screen three different types of material. The three guns and materials create red, blue and green color and by mixing these three any color can be created. Each of the color parts in a pixel is called a sub pixel and since the color screens need three colors each pixel consist of three sub pixels. In order to guide the different electro guns to the right part of the pixel a grille or mask is used depending on the layout of the sub pixels.

2.1 Frame rate

Since the electron guns only can illuminate one point at a time it needs to update the entire screen at least 24 times per second in order to minimize motion artifacts. In a normal CRT the frame rate is 25-29.97 Hz depending on the type of television system. In a modern television or computer screen the update frequencies is usually between 65-100 Hz and sometimes even more. This high frame rate is however also an effect of using progressive scanning. See chapter 2.3 for more information about progressive scanning. [Jac01, p. 8]

2.2 Sync signal

In the CRT the image is drawn as a series of sweeps or lines over the screen as shown in figure 2.1. For every new line the electro gun needs to be reset to the start of the line. This action requires a horizontal sync signal to be inserted between every line. Every time the last line of the screen is drawn the electro gun also needs to be reset to the top of the screen, for this a vertical sync signal is needed. [Jac01, p. 7]

2.3 Interlace and progressive scanning

Interlaced scanning is a way to reduce the bandwidth of the signal without too much loss of information. Instead of drawing all the lines in the image every time the image is updated, only every second line is updated. The signal contains two fields, one field contains the odd lines and one field the even lines. For example if the screen is updated at 25 Hz the signal needs to contain 25 full frames or 50 fields for each second.

The opposite to interlace scanning is the progressive scanning that draws all lines on the screen at each update. When using progressive scanning the frame rate needs to be higher or flicker can occur. This is usually solved in TV’s by doubling the update rate and showing one frame twice. The progressive scanning will also require more bandwidth since more data is needed at any given time.

When using interlaced scanning for the CRT the video is not perceived as de-graded but on screens with progressive scanning the video with interlaced scanning

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2.4 Gamma correction 9

can create artifacts in fast moving objects. This is because the two fields differ in time and creates a shift in the image for every second line. This distortion can be removed by using a filter but the end result will never be as good as progressive scanning. [Jac01, p. 8]

2.4 Gamma correction

The intensity of most displays is not linear to the input signal but instead propor-tional to some power, also called gamma. The non-linear transfer function results in the bright parts becoming extended and the dark parts compressed. However this effect can be used to minimize noise in transmission. The video signal is "gamma corrected" to have a linear output from the screen.

Since a channel with gamma corrected signal differs from one that is not cor-rected it is usually marked with an accent, for example R’. The transfer function from non-gamma corrected signal to gamma corrected signal is: Vout = Vinγ. In old systems gamma values between 2.2 and 2.8 were used but in modern systems a value of 1/0.45 is normally used. [Jac01, p. 32]

2.5 Color spaces

Color spaces are numerical representations of a set of colors. This representation can be made in many different ways. For computers the most commonly used representation is RGB and for video systems YIQ, YUV, Y+C, YPbPr and YCbCr are more common. However RGB is also used in video systems but is less common than the other color spaces. Not all color spaces are described in this section, instead an overview of the most common ones are given.

2.5.1 RGB

The RGB color space uses the three primary colors red, green and blue additively to create a desired color. This system is mostly used for computer graphics since the displays are usually directly connected to the computer and the signals and therefore bandwidth is not a problem.

In video systems the RGB system is not as good since it requires the same amount of bandwidth for each of the components. If the RGB color space would be used for television transmissions the bandwidth requirement would be much higher.

The RGB color space is also slower when manipulating video. For example changing the illumination of an image. For every pixel in the frame each color component in RGB needs to be read, edited and stored. In a system where illu-mination and color are separated this is much simpler since only the illuillu-mination needs to be edited. This optimizes some operations by 60 % when illumination is separated from color, however there are some operations that are faster with RGB but these are not as common. [Jac01, p. 15]

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2.5.2 YUV

The YUV color space contains a luminance value (Y) and two color values (U and V). This color space is used by PAL, NTSC and SECAM composite video systems. For monochromatic systems only the luminance value is used and the color parts have been added in such way that they do not interfere with the luminance. To convert from RGB to YUV the following equation is used [Jac01, p. 16]:

Y = 0.299 × R0_{+ 0.587 × G}0_{+ 0.114 × B}0

U = 0.492 × (B0_{− Y}0₎

V = 0.877 × (R0− Y0)

2.5.3 YIQ

The YIQ color space is used by some NTSC systems where the I stand for "in phase" and Q for "quadrature" referring to the transmission method used. To describe I and Q the UV part of the YUV color space can be seen as a plane with U and V as horizontal and vertical axes. The I and Q are then two new vectors in the plane rotated 33◦_{from U and V respectively. The YIQ can therefore be seen} as a YUV color space but with a change of basis. To convert from YUV to YIQ the following equation is used [Jac01, p. 17]:

I Q = 0 1 1 0 cos(33) sin(33) −sin(33) cos(33) U V

2.5.4 YPbPr

The YPbPr color space is similar to YUV but the color channels have been scaled to use more signal amplitude since the color space was developed for sending each component part separately. There are two different equations for SDTV and HDTV used to convert between RGB and YPbPr. The YCbCr color space is a digital version of the YPbPr color space.

2.6 Analog television system

In early analog broadcasting systems there were a need to transmit the video sig-nals on a radio frequency. As stated earlier the first screens where only monochro-matic screens and this means that only luminance and sound needed to be trans-mitted. The problem was solved by coding the video as the amplitude of a carrier frequency. The higher the amplitude, the more intensity on the current beaming point of the screen.

However when color needed to be added this resulted in the creating of some different systems around the world. Although different there are a few things all of them have in common. In the new system both the old monochromatic system

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2.6 Analog television system 11

Figure 2.2. A typical video signal line with sync, front and back porch, color burst and

video data.

and the new color system needed to be supported. To solve this problem the chrominance was added as a sub carrier frequency to the luminance and together they create a signal that works on both systems. Since most systems chose to use the YUV color space the color components U and V were combined into C and added to Y using the following equation:

C = U sin(ωt) + V cos(ωt) (2.1) The size of U and V in YUV were experimentally chosen so that when the U and V parts are added to Y they do not exceed the maximum and minimum levels for the monochromatic receivers. An excursion of 20% above or below the Y levels by a modulated sub carrier with U and V were found to be permitted.

The receiver of the video signal needs to have a reference burst for the C signal called color burst. When demodulating the signal it is compared to the color sync in order to find at what phase the chrominance signal is. See figure 2.2 for an example of a color line with sync, front and back porch, color burst and active video data.

The color burst is only present in color systems since it is only needed to enable the addition of color to a signal. In more modern signal types such as component signals the chrominance and luminance do not need to be mixed since they are sent on different channels. Because the signals are not modulated the color burst is not needed.

The different frame rates for each of the systems are linked to the frequency of the power grid in different countries. By matching the frame rate to the frequency of the power grid a type of interference that created rolling bars over the screen was avoided.

2.6.1 NTSC

In the USA a system called NTSC (National Television System Committee) was created for transmitting video signals but the first version had no support for color. At the time the frame rate was 30 Hz and it used 525 lines per image. After some

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debate about whether or not the new color system should be backward compatible with monochromatic screens it was decided that it should. A new standard was created based on the old with an adjustment of the frame rate to 29.97 Hz. A problem with NTSC is that it can create hue errors, or color shifts, under poor transmission conditions and is therefore sometimes referred to as "Never The Same Color". NTSC is used in several countries around the world including United States, Canada and Japan. [Jac01, p. 239]

2.6.2 PAL

PAL (Phase Alternating Line) system was created since the NTSC 60 Hz field rate did not match the 50 Hz power grid in Europe. In PAL the problem with color phase shift present in NTSC is solved by reversal of one of the phases every other line in the chrominance part, hence the name. In the beginning the system relied on the eye to average out the hue error but in later systems a delay line is implemented to combine the two phases in the chrominance. The PAL system uses 625 lines per frame and 50 Hz frame rate. [Jac01, p. 262]

2.6.3 SECAM

The SECAM (Sequentiel Couleur Avec Mémoire or "Sequential Color with Mem-ory") system was developed in France and is similar to PAL in that it uses 625 lines and 50 Hz but instead of sending chrominance as one combined part it sends each color part on every other line. Since this creates a problem when receiving the transmission a memory was added to the receiver to store the last line at the receiver in order to be able to mix all parts together.

Since the chrominance is sent on two different signals it uses the YDbDr color space instead of YUV in PAL and NTSC as this is better when the chrominance signal is separated. This color space is only a scaled version of YUV color space. The SECAM system is used in several parts of the world but is now being phased out and replaced by PAL or digital transmissions. [Jac01, p. 287]

2.7 Resolution

In the analog broadcasting system only one resolution was available but with digital broadcasting, signals can be transmitted in different screen resolutions de-pending on the source and screen used. The resolutions are referred to with a code. The first number is the number of horizontal lines and after this a letter depending on the type of scanning is added. For example "576i" refers to the size 720x576 and the letter "i" means that it uses interlaced scanning. If the last letter is a "p" it would mean that the source uses progressive scanning. One more number can be added after the scanning, for example "576i25" meaning 25 Hz frame rate.

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2.8 Analog video interfaces 13

2.7.1 Standard definition

Standard definition (SDTV) refers to the analog resolutions used in analog tele-vision systems. However in modern digital systems these resolutions can also be used. The resolutions are referred to as "480i" and "576i" for NTSC and PAL respectively. Only these two resolutions are referred to as PAL and NTSC. Even though higher resolutions share the size or frame rate these are not referred to as NTSC or PAL.

2.7.2 Enhanced definition

Enhanced definition (EDTV) uses the same resolution as in standard definition but instead of using interlaced scanning it uses progressive scanning. These resolutions are referred to as "480p" and "576p" for 59.94Hz and 50Hz respectively. Since every frame contains a full update of the screen the bandwidth needs to be twice as large as for SDTV.

2.7.3 High definition

High definition (HDTV) has been used as a name for many types of resolutions but nowadays the minimum resolution is "720p" for HDTV. The resolutions "1080i", "1080p" and "2160p" are all HDTV. However "2160p" and larger are not commonly used in commercial TV applications at the time of writing this thesis. The ITU institution describes HDTV in the following way:

"A high-definition system is a system designed to allow viewing at about three times the picture height, such that the system is virtually, or nearly, transparent to the quality of portrayal that would have been perceived in the original scene or performance by a discerning viewer with normal visual acuity." [ITU02b, p. 1]

2.8 Analog video interfaces

In old television systems the only way to receive a signal was through an antenna or cable. For modern television systems there are several different ways to receive a video signal with varying quality. All these connection types are a result of the introduction of devices connected to the TV such as VHS, DVD, STB and their need for better connection types.

2.8.1 Composite video

Composite video is the signal type used in analog SDTV signals before it is mod-ulated with an RF-signal and transmitted. The composite signal is sometimes referred to as CVBS where the letter refers to Color, Video, Blank and Sync. The signal is normally transmitted over a single cable with RCA connectors at each end. Sound is transmitted separately in either mono or stereo.

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2.8.2 S-Video

In a TV receiving a composite signal the signal is split into the luminance (Y) and chrominance (C) parts. However this separation is rarely perfect and to resolve this problem S-Video is similar to composite video but Y and C are separated into two different cables. The sync signals and other signals are sent on the Y cable together with the luminance. [Jac01, p. 66]

2.8.3 SCART

SCART, also known as Peritel or Euroconnector, is a connection type used in Eu-rope allowing transmission of composite, S-Video, RGB and stereo sound. However not all these signal types can be sent at the same time but composite and sound is always available. There are several different types of SCART cables and the pins at the connector are also used for different signals depending on the signal type is used. [Jac01, p. 67]

2.8.4 Component video

Component video refers to YPbPr and RGB since the three parts are separated and sent on different cables. YPbPr is sent on three cables with RCA or BNC connectors [Jac01, p. 77]. Sound is transmitted separately. The Y-channel con-tains the vertical and horizontal sync signals. RGB is most commonly sent over a SCART-cable but can be sent with three cables as YPbPr. Depending on the type of RGB signal the sync signals can be sent either on the green channel, on all channels or a separate signal is used as sync. [Jac01, p. 71]

2.9 Video signal composition

Any video signal, independent of the transmission type, is sent as a series of lines. In order to know where a line starts a horizontal sync signal is used. A vertical sync is also needed in order to know when a new frame or image is started. The vertical sync is a series of special lines and depending on the signal used these vary.

When creating a signal the first lines of the signal contain the vertical sync signal. After the vertical sync some empty lines are sent and then lines with actual image data are sent. If an interlaced signal is used a special type of vertical sync signal is used to mark where the second frame starts. After this, the second frame active image lines are sent. At the end of an image or field a series of equalizing pulses are sent to prepare for the vertical sync or field sync. These signals were used for old televisions to maintain the horizontal sync during the vertical sync.

In figure 2.3 and 2.4 the signal composition for NTSC and PAL respectively can be seen. Only a selection of the lines in an image is shown and the start of each vertical sync is marked with a vertical dashed line.

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2.9 Video signal composition 15

Figure 2.3. NTSC signal with vertical and horizontal sync signals [Ins07].

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Chapter

3

Evaluation of subjective measuring

methods

In this chapter a brief introduction into subjective measurement methods is given with an evaluation of the current status of the field.

3.1 Introduction

Several different methods for measuring quality are already available for video signals. Most of these methods are either adapted from methods to measure images or can be used for images, but the main focus in this thesis is video measurement. These measurement methods are for the most part used to assess codec quality. Although the main part of this report is about measuring low level analog video signals, some errors in the low level signals might not have any effect on the end users perception of image quality. And some errors might look insignificant at the low level but very perceivable by the end user.

In order to measure the actual video data using the analog video signal an image needs to be created for every frame. The transformation from analog video signal to the image based digital representation should be done in such a way that any distortion created in the transformation is minimized.

The simplest methods for measuring video and image quality are objective measures. These methods are usually straightforward and can prove usable for some types of codec’s and distortions but they are not perfectly matched with what a human perceives as good quality.

Because objective methods only work well in some cases subjective assessments were created as a way to use real persons and show images or video and have them rated according to some scale.

The most sophisticated method so far is a more advanced engineering approach that simulates the human visual system (HVS) called objective perceptual assess-ment.

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Another method is to use a mixture of both objective methods and subjec-tive assessments, called engineering approach. This method consists of different algorithms that search for distortions known to cause a lower score in subjective assessment.

3.2 Pixel to pixel

The most famous pixel based measurements are mean squared error (MSE) and signal-to-noise ratio (PSNR). The PSNR measurement is a logarithmic represen-tation of the MSE measurement [RR06]. These methods were originally used to compare two pictures but they can also be used for video, however MSE ignores all temporal movement and distortions in a video unless it leads to the creation of spatial distortions as well.

M SE = 1 X × Y Y X j=0 X X i=0 [Ai,j− Bi,j]2 (3.1) M SEvideo = 1 X × Y × T T X k=0 Y X j=0 X X i=0 [Ai,j,k− Bm,n,t]2 (3.2) P SN Rvideo= 10 log10M AX 2 I M SE (3.3)

The equations used for calculating of MSE and PSNR can be seen in equa-tion 3.1 to 3.3. Equaequa-tion 3.1 is used to calculate MSE for pictures of size X × Y and equation 3.2 is used for calculating MSE for video of size X ×Y with T frames. The last equation 3.3 is used to calculate the PSNR value for either movies or pic-tures, depending on which MSE is used. The value M AXI is the highest possible pixel value [RR06].

MSE based measurements are only a crude approximation of a human observer because it uses pixel to pixel comparison. Humans perceive the distortions differ-ently depending on the kind of distortion and it’s location. For instance the HVS is less sensitive to distortions in high frequency areas of the image compared to low frequency areas [WM08]. In figure 3.1 two images with the same PSNR value is shown. However the left image contains high frequency noise in the bottom part of the image and the right image side contain low frequency noise inserted into the top part of the image [RR06]. This shows that the PSNR value cannot always be trusted as a way to find distortions in images or videos.

Even though there are some problems with MSE, it is still widely used because of it’s simple design and computational speed [RR06]. Many scientists have also developed a familiarity with the correlation between different results and amount of distortions. Minimizing the MSE function is also relatively simple [WM08].

Although a number of different methods for pixel to pixel measurement have been tested and some of these have worked quite well for some compressions or type of distortion they were still not reliable across different techniques [RR06].

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3.3 Subjective assessment 19

Figure 3.1. Two images with the same PSNR value but different distortions.

3.3 Subjective assessment

Subjective assessment determines the quality or impairment of video by showing real persons a program-like video in sessions [ITU01]. The ITU has created a recommendation [ITU02a] for subjective assessment of television image quality. The recommendation contains information about viewing conditions, test material, observers, the different methods etc. This is the most used reference when making subjective assessments and is the main source of information for this section.

3.3.1 Preparations

There are two different types of subjective measures; one measures the quality under optimum conditions and one under non-optimum conditions. Non-optimum conditions occur when the image for example is distorted by packet-loss, bad transmission, etc. The optimum type is the only one we will look at since we are not interested in how the information is sent to the STB, only the conversion from digital to analog signals.

In order to conduct a subjective assessment in a way that it can be repeated and correct even when tested in other places ITU has created a list of viewing conditions. This defines what luminance is needed, distance to screen, room illu-mination etc.

Many different test material or test clips can be used depending on what kind of assessment performed. In any test at least some non-critical material and some critical material should be included. The critical material are of the type where distortions is more likely to appear and non-critical material is the opposite. Both are needed since it is not possible to extract information about critical performance from non-critical material but the other way is possible.

During the assessment at least 15 observers should be used and they should not be experts (i.e. they should not be working with quality assessment or other

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types of television quality). All observers should have their vision checked before any sessions. They should also be checked for normal color vision. These tests are performed in such a way that the results from the subjective assessment depend on the system under test and not the user’s vision. It is an important part of every session to instruct the observer the same way in order to minimize user errors. The least errors are produced when having a written explanation and after this any remaining questions are answered.

For every session there are some "dummy presentations" in the beginning show-ing the kinds of impairment that might be in the test. These "dummy presenta-tions" should not be included with the result as they are only used to stabilize the observer. A random order should be used for the videos during the subjective assessment in order to minimize the errors from switching between videos.

3.3.2 DSIS

The Double-Stimulus Impairment Scale (DSIS) method is a cyclic method that first show a reference video and then video from the device under test. Before, between and after any video a gray image is shown in order to remove any memory effects in the HVS. After the two videos the user is asked to vote according to a grading scale.

There is also a second method where the cycle is repeated twice and the voting is performed during the last cycle. This method is more time consuming but might be useful in cases where impairments are small.

The scale used in DSIS use words to describe the distortions and range from "Imperceptible" to "Very annoying". It should be noted that the lowest score on the grading scale is not necessarily contained in the set of images shown. Instead users should make an overall assessment of impairment and express these according to the wordings in the scale.

A session should only last as long as up to half an hour including any prepa-rations. If lasting longer the risk increases that the observer might get tired.

3.3.3 DSCQS

The Double-Stimulus Continuous Quality-Scale (DSCQS) is available in two dif-ferent variants. The first variant uses one observer and one screen where the user can switch between two different video streams. One video stream contains the reference and the other is the impaired video stream. The observer freely switches between the two videos until the user have a mental assessment of the quality of both video streams. After this the observer votes according to a scale.

In the second variant there are a number of observers watching the same screen and the streams are automatically switched between the two video streams. And after this the voting is performed. Both methods can be repeated several times depending on the length of the sequences.

The voting scale of DSCQS also use words to describe the distortions but differ from DSIS since it range from "Exellent" to "Bad". The scores from DSCQS should not be translated to those of DSIS as the span of DSCQS is not the same. Any

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3.3 Subjective assessment 21

score from the DSCQS method should not be interpreted as an absolute score but instead as a relative score between the two streams.

3.3.4 SSCQE

The Single Stimulus Continuous Quality Evaluation (SSCQE) is a result of digital television where impairments are scene-dependent and time-varying. The short sequences in DSIS and DSCQS might miss some of the impairment and therefore longer sequences are needed. A problem that occurs when using longer sequences is that humans tend to only vote on the last 10 to 15 second. To fix this problem votes are made during the whole sequence using a slider mechanism that samples the user’s voting twice a second.

In SSCQE no reference is shown and therefore it is important to make the observer aware of the correlation between the slider level and the voting scale. One problem with SSCQE is that there is a delay between a change in impairment and the change of the slider level. Another problem is the fact that humans quickly respond to negative changes to the image quality but is slow to revert back after these have disappeared.

3.3.5 SDSCE

The Simultaneous Double Stimulus for Continuous Evaluation (SDSCE) is a method that derives from SSCQE but have some differences in the presentation of video and the voting. The observers watch both the reference and the impaired video at the same time. If the format is small one screen can be used, otherwise two separate screens should be used. The observer should assess the difference between the two video streams and vote on the fidelity by use of a slider.

Before any session starts it is important that a training phase, a demonstra-tion session and a mock test should be conducted. The training phase should include written instructions to the observer in order to minimize any bias from the test administrator. During the demonstration session the observer should be made acquainted with the voting procedure. In the mock test different kinds of impairment should be included and after this has finished the test administrator should check that the voting from the mock test where the reference is shown on both screens are close to the top of the scale. If this is not so the session should be restarted and any questions from the observer answered.

3.3.6 Contextual effects

During any testing the sequences should be in a random order to minimize any contextual effects. However even if random orders are used this can still occur. If for example a strongly impaired video is shown after a series of less impaired videos, observers might rate this to a lower score than they would have otherwise. Some testing has been done on this and the best method to use is the DSCQS if minimal contextual effect is required. The DSIS and other comparing methods have evident effects and the method with most contextual effects is the DSIS version two.

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3.4 Objective perceptual measurements

The HVS is a very complex apparatus and so far, even thought much investigation has gone into this, there is still a lot to learn. However there are a number of psychophysical effects that have been isolated as more or less important. These effects are carried out more or less as a sequential process [RR06, p. 160].

3.4.1 Color processing

One of the first stages is when the light hits the eye and is received by the rods and cones in the retina. The rods are highly sensitive to low light and do not contribute much to the color vision. Cones on the other hand are less sensitive to light and are available in three types, short wavelength sensitive S-cones, middle wavelength sensitive M-cones and long wavelength sensitive L-cones. These three types of cones make up the color vision of the eye but each cone is color blind in the way that it loses all information about any wavelength. However since there are three different types of cones the eye can match any color by the use of trichromacy.

In the model this is simulated by dividing any image into one achromatic and two chromatic channels. In this step the luminance-masking or lightness non-linearity of the HVS can also be taken care of by a filter. [RR06, p. 161]

3.4.2 Multi-channel processing

The HVS is tuned to different ranges of spatial frequencies which are separated into different channels. This separation can be created by a multi-resolution filter bank such as the cortex transform [Wat87]. This transform can be adjusted over a wide range and is quite flexible. Wavelet decomposition can also be used for the same effect and have the advantage of being simple to implement in a computer.

There are also one or two temporal low-pass filters and a temporal band-pass filter used to process different object velocities and temporal frequencies. [RR06, p. 161]

3.4.3 Contrast adaptation

The Weber-Fechner law states that the response of an HVS is not dependent on the absolute level of luminance but instead on what relation it has to the surrounding background. Contrast is defined as this relative variation but is quite difficult to model in the HVS as it varies depending on the location in the image. The per-ceived contrast is also sensitive to the luminance and color of the location. [RR06, p. 161]

3.4.4 Contrast sensitivity

One of the most important parts in the HVS is the contrast sensitivity function (CSF) which shows a correlation between the spatial frequency and the perceived contrast. As the spatial frequencies get higher the contrast decreases, but in color

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3.5 Engineering approach 23

images the CFS is more complex. This problem is usually solved by using a different CFS for each channel.

The HVS is also sensitive to temporal frequencies and can be described by temporal sensitivity functions. These have the form of a low-pass or band-pass filter. There is also an interaction between the spatial and the temporal filter described by the spatio-temporal sensitivity functions. [RR06, p. 162]

3.4.5 Masking effects

Sometimes one stimulus can’t be detected because of the presence of another, see the left image in figure 3.1 for example. And sometimes a stimulus cannot be seen without the presence of another, this is called facilitation. There are several different types of masking including the following: contrast masking, edge masking, texture masking and temporal masking. [RR06, p. 162]

3.4.6 Pooling effects

The last stage in the brain is where the information from different channels is collected together, this is called pooling. There is not much known about this process but often this is simulated by a summing over all channels to get a single rating of distortion. [RR06, p. 161]

3.5 Engineering approach

Although methods based on objective perceptual measurements are potentially more accurate they might sometimes be more versatile than necessary. The engi-neering approach is a way of creating algorithms in which prior knowledge about compression artifacts and simple vision models are used to find any impairment to the video. This approach might not be as versatile but can sometimes be very precise and effective for a given application area. Some examples of engineer-ing approach is to look at video blockengineer-ing effect, color bleedengineer-ing, staircase effects, ringing, etc.

3.6 Metric comparison

It is generally accepted that the best method to use is a subjective assessment but in some cases there might not be enough time or resources to conduct such a test. In these cases some sort of automatic algorithm is needed.

There are many different methods available for each of the different test cate-gories, but any attempt to find the best one of these would only lead to a lot of unnecessary implementation. In order to find which of all the test methods are the best to use, the Video Quality Experts Group (VQEG) has started doing tests of a lot of different methods. Their first test was conducted between 1997 and 2000 as phase one. Ten different methods were tested and compared both against each other but also against PSNR. The result showed that:

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• No model could replace subjective assessment.

• No model outperformed any of the other in all conditions.

• No model outperformed PSNR in all conditions.

A second test, phase two, was conducted between 2000 and 2004 as a follow-up of the first phase. The second phase used a much broader field of distortions and focused on distribution of digital media. Six different methods were evaluated by the VQEG in contrast to the first tests that were conducted by the creators individually. The result of the test was that four method performed better than PSNR and one methods correlated to 94% of the subjective assessments [RR06, p. 171]. This is much better than the PSNR with only 70% correlation to subjective assessments. The four best methods are:

• NTIA / ITS

• British Telecom

• Yonsei University / SK Telecom

• CPqD

Although this is a very good result for the testing it still shows that it is better to use subjective assessment than any objective methods. However there is a very small difference between the two and in some instances it might be better to use objective perceptual measurements. There is still a lot to be done in order to fully remove the need for any humans in the testing of video quality in a product.

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Chapter

4

The sampling system

In this chapter a brief explanation is made of the overall system used for sampling analog signals and how this connects to the computer. Since this thesis is a continuation of a thesis by Löfgren [Löf08] in which the sampling system was created, any information about the sampling system not found in this section can be found there. The video sampling hardware is referred to as VSH further on.

4.1 Overall system design

The VSH has a connection for a SCART cable and four RCA connectors. These are connected to an STB or other device to be measured. The device under test, DUT, is setup in such way that it outputs a special test image signal. The VSH is connected to a computer via USB and on the computer a video quality mea-surement program, called MOViA, is running. This is connected to the VSH via the USB port and requests information and does all the measuring on the signal received. See figure 4.1 for visualization of the overall system design.

Figure 4.1. Overview of the video sampling system.

4.2 VSH design

The VSH consists of a specifically designed PCB assembly with a Spartan 3 FPGA as the main processor. Connected to the FPGA are four 12-bit high speed

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to-digital converters, also called ADC. The FPGA is clocked at 100 MHz and samples the ADC at 100 MSPS into two 36 bit wide synchronous SRAM with 16 Mbit each. Each memory stores two channels, one channel from bit 0 to 11 and another from bit 12 to 23. Since there are 12 bits still available per memory some extra data could be stored in these bits, but at the moment no such function is available. A total of 444444 samples or 4,44 ms can be stored in RAM since the sampling speed is 100 MSPS.

Four channels are available to the VSH because sampling of RGB requires all four channels. The RGB signals do not contain any sync signal and therefore sync information is extracted from the composite signal from the SCART. If the sync signal would be contained inside the RGB signal only three channels wold be needed. For YPbPr only three signals are needed since the sync is sent on the Y channel. Since there are only four ADC and two different signal types a video multiplexer is available to select if signals from the SCART or RCA connectors should be sampled.

A sample rate of 100 MSPS is required since the highest bandwidth in the video signals reach 30 MHz and in order to sample these correctly a sample rate of at least 60 MSPS would be needed to avoid aliasing as stated in the Nyquist-Shannon sampling theorem. By using an even higher sampling rate than 60 MSPS the aliasing is minimized even more.

Figure 4.2. Overview of the video sampling hardware.

4.3 VSH to computer communication

In order to communicate with the computer an FTDI FT245R in the VSH is used to translate the parallel signals to USB signals. On the computer side a special

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4.3 VSH to computer communication 27

driver is used to communicate with the FT245R. This driver is supplied by FTDI and cannot be changed.

The FT245R chip can only handle 8 bit data and therefore a special communi-cation protocol is used, for more information about the protocol see the previous thesis [Joh07, p. 10] [Löf08, p. 35].

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Chapter

5

Problem analysis

In this chapter the problem of creating a video signal quality measuring software is investigated and what requirements are needed.

5.1 Vision of operation

The system as a whole is to be used as a tool for assessing the quality of analog video signals from an STB. There is a need for it to be fast, simple and easy to configure. Above all it needs to be very robust and correct in it’s measurements since the measurements made will guide the further development of the STB.

5.2 Measurement procedure

During any signal quality measurement a static image or video stream is played by the DUT. Depending on the type of DUT this can be performed in different ways. The video or image information is converted in the DUT to a series of lines and sent out via RGB or YPbPr signals to the VSH where it is sampled by the ADC’s. The image or video stream contains all the patterns needed for all the measurements methods. The different patterns are present over several lines in order to minimize any distortion between the different types of patterns. All measurements should be made as close to the vertical middle of a pattern in order to minimize this type of distortion.

A set of test patterns for both RGB and YPbPr were already available at the start of the thesis. The test pattern used cannot be included with the thesis due to copyright issues. However an example of a test pattern for only RGB is shown in figure 5.1. The different types of patterns in order from top to bottom are: color bar, multiburst, short-time distortion, non-linearity, shallow ramp, 100 % level and 0 % level.

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Figure 5.1. An example of a test pattern used for testing distortions.

5.3 Video distortion types

There are many different types of distortions that can occur in a video signal but not all of them affect the perceived quality of the image. In order to measure the quality of any video there is a need to know the most common distortions. All of the distortion types in this list are well known and are generally measured when evaluating video quality.

As described earlier there where already a set of test patterns available at the start of the thesis and this limited the amount of distortion types that could be tested. However since the distortions types available to measure the quality of a signal cover the basic test needed in order to evaluate a device, no new distortion types were researched. Because of this the list is not by any means exhaustive or sorted in any order.

5.3.1 Level error

The levels in the video signal are specified to certain values and if these are not reproduced correctly color shifts and/or illumination errors can occur in the video. A simple way to test for errors in the levels is to analyze a line with some color bars and check these against their specified values. This test allows the user to test the level and if necessary correct this before continuing to other tests since a level error can affect other tests.

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5.3 Video distortion types 31

5.3.2 Frequency response distortion

If the frequency response of a DUT is not correct several different types of signal distortions can occur. The frequency distortions can affect the image in many different ways depending on the type. [PAL99, p. 31] These types of distortions are usually tested with a line of sinusoidal form with increasing frequency over the length of the line. Another way to test the frequency response is by using a few isolated frequency bursts of different frequencies on a line, also called multiburst. When assessing the quality of frequency response the amplitude and final frequency is the most interesting.

5.3.3 Non-linearity

If a DUT creates amplitude dependent distortions this is often referred to as non-linearity distortions. Small distortions in the illumination is not noticed by most people but if larger non-linear distortions exist this can be seen as crushing and clipping of illumination [PAL99, p. 50]. Distortions in color channels can result in color shifts which can be more noticeable. This type of distortion can be measured with a line containing ramps from the lowest value to the highest value possible for the each of the channels.

5.3.4 Noise

Noise is in this context electronic noise usually created as an effect of thermal noise and results in grainy or snowy image [PAL99, p. 58]. The addition of noise in a video signal can in low frequency areas give distortions but in more high frequency areas this distortion might not be noticed, see figure 3.1 in chapter 3.

However since this distortion is visible in low frequency parts and gives a good overall evaluation of the DUT this is a very interesting measurement. The simplest way to measure the noise in a signal is to use a line with a constant signal since any errors in the line must be from noise. However this measurement can miss some low frequency noise and quantization noise in the signal and therefore another measurement is made on a line with a slowly rising ramp. [ITU90, p. 10]

5.3.5 Short time distortion

Short time distortions are distortions created in fast changing parts of the signal. Either by insertion of delays, overshoots, undershoots or long settling times in the signal. The distortions can on the image level be seen as fuzzy vertical edges and ringing that can create distortions in the chrominance near vertical edges [Glo01, p. 151].

In order to measure these distortions a line with a short pulse and a "bar" is used. The bar is a long vertical part with the same color, in this instance it is white, see pattern three in figure 5.1. This type of measurement is called K2T measurement since the pulse is 2T wide where T is proportional to the bandwidth of the signal. A K2T-value of 3 % is noticeable by most people and for SDTV signals a maximum limit of 3 % K2T-value is specified by ITU. [ITU90, p. 36]

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5.3.6 Channel delay

Channel delays are created when one or more channels in a component video signal are delayed relative to another channel. This distortion can result in distortion of edges depending on how large the delay is [Glo01, p. 4].

The delay can be a result of different signal path lengths for each of the channels or inequality of components. To measure this delay any type of signal with equal signal on all channels can be used, however the simplest signal is a frequency sweep since this tests all frequencies at once. [Glo01, p. 47]

5.3.7 Sync delay and amplitude distortions

Delay and amplitude errors in sync signals can give a wide range of errors. However some distortions can occur without notice since most televisions correct for small distortions in sync signals. Measuring sync delays is done on any line and if back and front porch length and amplitude measurements are needed a signal with at least some amplitude above black level is needed in order to detect what part is active signal and not.

5.3.8 Spatial distortion

This type of distortion is usually caused by undesired rescaling, cropping or off-set in the video image. To measure any spatial distortions a comparison among each point in the video and a reference image is needed. If the video image is unevenly rescaled objects in view can appear stretched or compressed. Cropping can remove important parts of video images such as subtitles or other important information. [Glo01, p. 88]

5.3.9 Horizontal sync jitter and wander

Jitter is a short-term instability of a signal compared to a perfect reference and wander is a long-term drift of a signal in the range of 10 to 20 Hz. This type of distortion can lead to sync problems. [Glo01, p. 92]

5.3.10 Crosstalk

Crosstalk is created when two or more channels affect each other in such a way that the signals from one channel is mixed with another by some amount. This can lead to ghost effects in the image from both illumination and colors depending on the type of distortion [Glo01, p. 42]. Crosstalk is measured by sending some type of signal on only one channel, leaving the other two blank and measuring these two for any change in the signal. This measurement is repeated two times until all channels have been used as a source for the cross-talk.

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5.4 Selection of distortions types to evaluate 33

5.4 Selection of distortions types to evaluate

Since there is only a limited amount of time for this work only some of all dis-tortion types will be assessed in this thesis. And since the test-signal patterns already existed there were a limited number of measurements that could be used. Depending on the probability of a distortion and it’s effect when occurring a few distortions types have been selected for measurement development. The selected distortions to be evaluated are:

• Level error

• Frequency response distortions

• Non-linearity

• Noise

• Short time distortions

• Horizontal sync delay and sync amplitude distortions

The level error has been selected since it affects other measurements and is the most probable error to exist in a video signals. Frequency response distortions can also affect many other measurements and gives a good representation of the system as a whole. Non-linearity distortions have been selected since it can give noticeable errors in the signal. Noise can affect some types of signals but not all. However it gives a good representation of the quality of a signal. Short time distortions have been selected since these types of distortions can affect the signal and is more usual in HDTV signals because of the higher bandwidth. Horizontal sync delay and amplitude distortions are very simple to measure and are therefore also evaluated.

5.5 Requirements

This chapter contains a list of requirement on the software to be developed. By using detailed and exact requirement the development process is simplified since unnecessary implementation is minimized. Which of these requirements where eventually implemented can be seen in chapter 9.

R0 Example requirement

This example illustrates what a requirement looks like. Each re-quirement has a unique number, a title and a more extensive ex-planation and in some cases a motivation behind the requirement.

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5.5.1 General requirements

These requirements are not specific to any part of the program but indirectly affect the software development.

R1 Sampling hardware

Video signals should be sampled by the pre-existing hardware.

R2 Video sample transfer

Sampled video signals should be transferred from sampling hard-ware to PC.

R3 Subjective analysis

A small study of implementing subjective analysis should be conducted.

R4 Comparison to existing equipment

The final product should be compared to existing commercial video analysis equipment.

5.5.2 Measurement requirements

The requirements in this section are used to perform parts of the signal quality measurements.

R5 YPbPr video

The software should be able to sample and measure YPbPr video at 1080i, 720p, 576p and 480p.

R6 RGB

The software should be able to sample and measure RGB video at 576i and 480i.

Design and Implementation of an Analog Video Signal Quality Measuring Software for Component Video

Institutionen för systemteknik

Department of Electrical Engineering

Examensarbete

Design and Implementation of an Analog Video

Signal Quality Measuring Software for Component

Video

Design and Implementation of an Analog Video

Signal Quality Measuring Software for Component

Video

Examensarbete utfört i Informationskodning

vid Tekniska högskolan i Linköping

av

Abstract

Acknowledgments

Contents

List of Figures

List of Tables

Chapter

1

Introduction

1.1

Background

1.2

Purpose

1.3

Delimitations

1.4

Method

1.5

Document overview

1.6

Reading instructions

1.7

Glossary

Chapter

2

Analog video signal theory

2.1

Frame rate

2.2

Sync signal

2.3

Interlace and progressive scanning

2.4

Gamma correction

2.5

Color spaces

2.5.1

RGB

2.5.2

YUV

2.5.3

YIQ

2.5.4

YPbPr

2.6

Analog television system

2.6.1

NTSC

2.6.2

PAL

2.6.3

SECAM

2.7

Resolution

2.7.1

Standard definition

2.7.2

Enhanced definition

2.7.3

High definition

2.8

Analog video interfaces

2.8.1

Composite video

2.8.2

S-Video

2.8.3

SCART