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Cover image for Digital video image quality and perceptual coding
Title:
Digital video image quality and perceptual coding
Publication Information:
Boca Raton, FL : CRC Press, 2006
ISBN:
9780824727772

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30000010164301 TK6680.5 D53 2006 Open Access Book Book
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Summary

Summary

The hand is quicker than the eye. In many cases, so is digital video. Maintaining image quality in bandwidth- and memory-restricted environments is quickly becoming a reality as thriving research delves ever deeper into perceptual coding techniques, which discard superfluous data that humans cannot process or detect. Surveying the topic from a Human Visual System (HVS)-based approach, Digital Video Image Quality and Perceptual Coding outlines the principles, metrics, and standards associated with perceptual coding, as well as the latest techniques and applications.

This book is divided broadly into three parts. First, it introduces the fundamental theory, concepts, principles, and techniques underlying the field, such as the basics of compression, HVS modeling, and coding artifacts associated with current well-known techniques. The next section focuses on picture quality assessment criteria; subjective and objective methods and metrics, including vision model based digital video impairment metrics; testing procedures; and international standards regarding image quality. Finally, practical applications come into focus, including digital image and video coder designs based on the HVS as well as post-filtering, restoration, error correction, and concealment techniques.

The permeation of digital images and video throughout the world cannot be understated. Nor can the importance of preserving quality while using minimal storage space, and Digital Video Image Quality and Perceptual Coding provides the tools necessary to accomplish this goal.

Instructors and lecturers wishing to make use of this work as a textbook can download a presentation of 786 slides in PDF format organized to augment the text.

accompany our book
(H.R. Wu and K.R. Rao, Digital Video Image Quality and Perceptual Coding, CRC Press (ISBN: 0-8247-2777-0), Nov. 2005)
for lecturers or instructor to use for their classes if they use the book.


Table of Contents

List of Contributorsp. ix
Acknowledgmentsp. xi
Prefacep. xiii
I Picture Coding and Human Visual System Fundamentalsp. 1
1 Digital Picture Compression and Coding Structurep. 3
1.1 Introduction to Digital Picture Codingp. 3
1.2 Characteristics of Picture Datap. 6
1.3 Compression and Coding Techniquesp. 12
1.4 Picture Quantizationp. 21
1.5 Rate-Distortion Theoryp. 25
1.6 Human Visual Systemsp. 26
1.7 Digital Picture Coding Standards and Systemsp. 31
1.8 Summaryp. 40
2 Fundamentals of Human Vision and Vision Modelingp. 45
2.1 Introductionp. 45
2.2 A Brief Overview of the Visual Systemp. 45
2.3 Color Visionp. 47
2.4 Luminance and the Perception of Light Intensityp. 55
2.5 Spatial Vision and Contrast Sensitivityp. 59
2.6 Temporal Vision and Motionp. 75
2.7 Visual Modelingp. 80
2.8 Conclusionsp. 81
3 Coding Artifacts and Visual Distortionsp. 87
3.1 Introductionp. 87
3.2 Blocking Effectp. 88
3.3 Basis Image Effectp. 91
3.4 Blurringp. 93
3.5 Color Bleedingp. 93
3.6 Staircase Effectp. 96
3.7 Ringingp. 97
3.8 Mosaic Patternsp. 99
3.9 False Contouringp. 102
3.10 False Edgesp. 104
3.11 MC Mismatchp. 106
3.12 Mosquito Effectp. 108
3.13 Stationary Area Fluctuationsp. 110
3.14 Chrominance Mismatchp. 112
3.15 Video Scaling and Field Rate Conversionp. 113
3.16 Deinterlacingp. 116
3.17 Summaryp. 119
II Picture Quality Assessment and Metricsp. 123
4 Video Quality Testingp. 125
4.1 Introductionp. 125
4.2 Subjective Assessment Methodologiesp. 126
4.3 Selection of Test Materialsp. 126
4.4 Selection of Participants - Subjectsp. 128
4.5 Experimental Designp. 129
4.6 International Test Methodsp. 132
4.7 Objective Assessment Methodsp. 150
4.8 Summaryp. 151
5 Perceptual Video Quality Metrics - A Reviewp. 155
5.1 Introductionp. 155
5.2 Quality Factorsp. 156
5.3 Metric Classificationp. 157
5.4 Pixel-Based Metricsp. 159
5.5 The Psychophysical Approachp. 160
5.6 The Engineering Approachp. 165
5.7 Metric Comparisonsp. 170
5.8 Conclusions and Perspectivesp. 172
6 Philosophy of Picture Quality Scalep. 181
6.1 Objective Picture Quality Scale for Image Codingp. 181
6.2 Application of PQS to a Variety of Electronic Imagesp. 202
6.3 Various Categories of Image Systemsp. 209
6.4 Study at ITUp. 213
6.5 Conclusionp. 218
7 Structural Similarity Based Image Quality Assessmentp. 225
7.1 Structural Similarity and Image Qualityp. 225
7.2 The Structural SIMilarity (SSIM) Indexp. 228
7.3 Image Quality Assessment Based on the SSIM Indexp. 233
7.4 Discussionsp. 236
8 Vision Model Based Digital Video Impairment Metricsp. 243
8.1 Introductionp. 243
8.2 Vision Modeling for Impairment Measurementp. 247
8.3 Perceptual Blocking Distortion Metricp. 258
8.4 Perceptual Ringing Distortion Measurep. 269
8.5 Conclusionp. 275
9 Computational Models for Just-Noticeable Differencep. 281
9.1 Introductionp. 281
9.2 JND with DCT Subbandsp. 285
9.3 JND with Pixelsp. 294
9.4 JND Model Evaluationp. 298
9.5 Conclusionsp. 299
10 No-Reference Quality Metric for Degraded and Enhanced Videop. 305
10.1 Introductionp. 305
10.2 State-of-the-Art for No-Reference Metricsp. 306
10.3 Quality Metric Components and Designp. 307
10.4 No-Reference Overall Quality Metricp. 313
10.5 Performance of the Quality Metricp. 317
10.6 Conclusions and Future Researchp. 321
11 Video Quality Experts Groupp. 325
11.1 Formationp. 325
11.2 Goalsp. 326
11.3 Phase Ip. 326
11.4 Phase IIp. 330
11.5 Continuing Work and Directionsp. 332
11.6 Summaryp. 332
III Perceptual Coding and Processing of Digital Picturesp. 335
12 HVS Based Perceptual Video Encodersp. 337
12.1 Introductionp. 337
12.2 Noise Visibility and Visual Maskingp. 338
12.3 Architectures for Perceptual Based Codingp. 340
12.4 Standards-Specific Featuresp. 352
12.5 Salience/Maskability Pre-Processingp. 357
12.6 Application to Multi-Channel Encodingp. 358
13 Perceptual Image Codingp. 361
13.1 Introductionp. 361
13.2 A Perceptual Distortion Metric Based Image Coderp. 368
13.3 Model Calibrationp. 377
13.4 Performance Evaluationp. 394
13.5 Perceptual Lossless Coderp. 412
13.6 Summaryp. 419
14 Foveated Image and Video Codingp. 431
14.1 Foveated Human Vision and Foveated Image Processingp. 431
14.2 Foveation Methodsp. 434
14.3 Scalable Foveated Image and Video Codingp. 440
14.4 Discussionsp. 452
15 Artifact Reduction by Post-Processing in Image Compressionp. 459
15.1 Introductionp. 459
15.2 Image Compression and Coding Artifactsp. 461
15.3 Reduction of Blocking Artifactsp. 465
15.4 Reduction of Ringing Artifactsp. 482
15.5 Summaryp. 484
16 Reduction of Color Bleeding in DCT Block-Coded Videop. 489
16.1 Introductionp. 489
16.2 Analysis of the Color Bleeding Phenomenonp. 490
16.3 Description of the Post-Processorp. 495
16.4 Experimental Results - Concluding Remarksp. 499
17 Error Resilience for Video Coding Servicep. 503
17.1 Introduction to Error Resilient Coding Techniquesp. 503
17.2 Error Resilient Coding Methods Compatible with MPEG-2p. 504
17.3 Methods for Concealment of Cell Lossp. 513
17.4 Experimental Procedurep. 523
17.5 Experimental Resultsp. 524
17.6 Conclusionsp. 527
18 Critical Issues and Challengesp. 543
18.1 Picture Coding Structuresp. 543
18.2 Vision Modeling Issuesp. 554
18.3 Spatio-Temporal Masking in Video Codingp. 558
18.4 Picture Quality Assessmentp. 559
18.5 Challenges in Perceptual Coder Designp. 562
18.6 Codec System Design Optimizationp. 566
18.7 Summaryp. 566
A VQM Performance Metricsp. 575
A.1 Metrics Relating to Model Prediction Accuracyp. 576
A.2 Metrics Relating to Prediction Monotonicity of a Modelp. 580
A.3 Metrics Relating to Prediction Consistencyp. 581
A.4 MATLAB Source Codep. 583
A.5 Supplementary Analysesp. 591
Indexp. 595
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