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Digital Video Image Quality and Perceptual Coding




ISBN 9780824727772
Published November 18, 2005 by CRC Press
640 Pages - 153 B/W Illustrations

 
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Book Description

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

PICTURE CODING AND HUMAN VISUAL SYSTEM FUNDAMENTALS
Digital Picture Compression and Coding Structure
. Introduction to Digital Picture Coding
. Characteristics of Picture Data
. Compression and Coding Techniques
. Picture Quantization
. Rate-Distortion Theory
. Human Visual Systems
. Digital Picture Coding Standards and Systems
. Summary
Fundamentals of Human Vision and Vision Modeling
. Introduction
. A Brief Overview of the Visual System
. Color Vision
. Luminance and the Perception of Light Intensity
. Spatial Vision and Contrast Sensitivity
. Temporal Vision and Motion
. Visual Modeling
. Conclusions
Coding Artifacts and Visual Distortions
. Introduction
. Blocking Effect
. Basis Image Effect
. Blurring
. Color Bleeding
. Staircase Effect
. Ringing
. Mosaic Patterns
. False Contouring
. False Edges
. MC Mismatch
. Mosquito Effect
. Stationary Area Fluctuations
. Chrominance Mismatch
. Video Scaling and Field Rate Conversion
. Deinterlacing
. Summary

PICTURE QUALITY ASSESSMENT AND METRICS
Video Quality Testing
. Introduction
. Subjective Assessment Methodologies
. Selection of Test Materials
. Selection of Participants-Subjects
. Experimental Design
. International Test Methods
. Objective Assessment Methods
. Summary
Perceptual Video Quality Metrics-A Review
. Introduction
. Quality Factors
. Metric Classification
. Pixel-Based Metrics
. The Psychophysical Approach
. The Engineering Approach
. Metric Comparisons
. Conclusions and Perspectives
Philosophy of Picture Quality Scale
. Objective Picture Quality Scale for Image Coding
. Application of PQS to a Variety of Electronic Images
. Various Categories of Image Systems
. Study at ITU
. Conclusion
Structural Similarity Based Image Quality Assessment
. Structural Similarity Based Image Quality
. The Structural SIMilarity (SSIM) Index
. Image Quality Assessment Based on the SSIM Index
. Discussions
Vision Model Based Digital Video Impairment Metrics
. Introduction
. Vision Modeling for Impairment Measurement
. Perceptual Blocking Distortion Metric
. Perceptual Ringing Distortion Measure
. Conclusion
Computational Models for Just-Noticeable Difference
. Introduction
. JND with DCT Subbands
. JND with Pixels
. JND Model Evaluation
. Conclusions
No-Reference Quality Metric for Degraded and Enhanced Video
. Introduction
. State-of-the-Art for No-Reference Metrics
. Quality Metric Components and Design
. No-Reference Overall Quality Metric
. Performance of the Quality Metric
. Conclusions and Future Research
Video Quality Experts Group
. Formation
. Goals
. Phase I
. Phase II
. Continuing Work and Directions
. Summary

PERCEPTUAL CODING AND PROCESSING OF DIGITAL PICTURES
HVS Based Perceptual Video Encoders
. Introduction
. Noise Visibility and Visual Masking
. Architectures for Perceptual Based Coding
. Standards-Specific Features
. Salience/Maskability Pre-Processing
. Application to Multi-Channel Encoding
Perceptual Image Coding
. Introduction
. A Perceptual Distortion Metric Based Image Coder
. Model Calibration
. Performance Evaluation
. Perceptual Lossless Coder
. Summary
Foveated Image and Video Coding
. Foveated Human Vision and Foveated Image Processing
. Foveation Methods
. Scalable Foveated Image and Video Coding
. Discussions
Artifact Reduction by Post-Processing in Image Compression
. Introduction
. Image Compression and Coding Artifacts
. Reduction of Blocking Artifacts
. Reduction of Ringing Artifacts
. Summary
Reduction of Color Bleeding in DCT Block-Coded Video
. Introduction
. Detailed Analysis of the Color Bleeding Phenomenon
. Description of the Post-Processor
. Experimental Results-Concluding Remarks
Error Resilience for Video Coding Service
. Introduction to Error Resilient Coding Techniques
. Error Resilient Coding Methods Compatible with MPEG-2
. Methods for Concealment of Cell Loss
. Experimental Procedure
. Experimental Results
. Conclusions
Critical Issues and Challenges
. Picture Coding Structures
. Vision Modeling Issues
. Spatio-Temporal Masking in Video Coding
. Picture Quality Assessment
. Challenges in Perceptual Coder Design
. Codec System Design Optimization
. Summary
Appendix: VQM Performance Metrics
. Metrics Relating to Model Prediction Accuracy
. Metrics Relating to Prediction Monotonicity of a Model
. Metrics Relating to Prediction Consistency
. MATLAB® Source Code
. Supplementary Analyses
INDEX

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