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Image and Video Compression for Multimedia Engineering: Fundamentals, Algorithms, and Standards, Third Edition 3rd edition [Hardback]

(Mitsubishi Electric Research Lab, Cambridge, Massachusetts, USA), (New Jersey Institute of Technology, Newark, USA)
  • Formāts: Hardback, 664 pages, height x width: 254x178 mm, weight: 1401 g, 280 Illustrations, black and white
  • Sērija : Image Processing Series
  • Izdošanas datums: 20-Mar-2019
  • Izdevniecība: CRC Press
  • ISBN-10: 1138299596
  • ISBN-13: 9781138299597
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Image and Video Compression for Multimedia Engineering: Fundamentals, Algorithms, and Standards, Third Edition 3rd editionPalielināt
  • Formāts: Hardback, 664 pages, height x width: 254x178 mm, weight: 1401 g, 280 Illustrations, black and white
  • Sērija : Image Processing Series
  • Izdošanas datums: 20-Mar-2019
  • Izdevniecība: CRC Press
  • ISBN-10: 1138299596
  • ISBN-13: 9781138299597
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9781138299597.html
Keywords:
"The latest edition provides a comprehensive foundation for image and video compression. It covers HEVC/H.265 and future video coding activities, in addition to Internet Video Coding. The book features updated chapters and content, along with several newchapters and sections. It adheres to the current international standards, including the JPEG standard"--

The latest edition provides a comprehensive foundation for image and video compression. It covers HEVC/H.265 and future video coding activities, in addition to Internet Video Coding. The book features updated chapters and content, along with several new chapters and sections. It adheres to the current international standards, including the JPEG standard.

Preface to the Third Edition xxiii
Acknowledgments xxv
Authors xxvii
Part I Fundamentals
1 Introduction
3(30)
1.1 Practical Needs for Image and Video Compression
4(1)
1.2 Feasibility of Image and Video Compression
5(15)
1.2.1 Statistical Redundancy
5(5)
1.2.1.1 Spatial Redundancy
5(3)
1.2.1.2 Temporal Redundancy
8(1)
1.2.1.3 Coding Redundancy
9(1)
1.2.2 Psychovisual Redundancy
10(10)
1.2.2.1 Luminance Masking
11(3)
1.2.2.2 Texture Masking
14(1)
1.2.2.3 Frequency Masking
14(1)
1.2.2.4 Temporal Masking
14(2)
1.2.2.5 Color Masking
16(3)
1.2.2.6 Color Masking and Its Application in Video Compression
19(1)
1.2.2.7 Summary: Differential Sensitivity
20(1)
1.3 Visual Quality Measurement
20(7)
1.3.1 Subjective Quality Measurement
21(1)
1.3.2 Objective Quality Measurement
22(5)
1.3.2.1 Signal-to-Noise Ratio
22(1)
1.3.2.2 An Objective Quality Measure Based on Human Visual Perception
23(4)
1.4 Information Theory Results
27(3)
1.4.1 Entropy
27(1)
1.4.1.1 Information Measure
27(1)
1.4.1.2 Average Information per Symbol
28(1)
1.4.2 Shannon's Noiseless Source Coding Theorem
28(1)
1.4.3 Shannon's Noisy Channel Coding Theorem
29(1)
1.4.4 Shannon's Source Coding Theorem
29(1)
1.4.5 Information Transmission Theorem
30(1)
1.5 Summary
30(1)
Exercises
31(1)
References
32(1)
2 Quantization
33(26)
2.1 Quantization and the Source Encoder
33(2)
2.2 Uniform Quantization
35(10)
2.2.1 Basics
36(4)
2.2.1.1 Definitions
36(2)
2.2.1.2 Quantization Distortion
38(1)
2.2.1.3 Quantizer Design
39(1)
2.2.2 Optimum Uniform Quantizer
40(5)
2.2.2.1 Uniform Quantizer with Uniformly Distributed Input
40(2)
2.2.2.2 Conditions of Optimum Quantization
42(1)
2.2.2.3 Optimum Uniform Quantizer with Different Input Distributions
43(2)
2.3 Nonuniform Quantization
45(4)
2.3.1 Optimum (Nonuniform) Quantization
45(1)
2.3.2 Companding Quantization
45(4)
2.4 Adaptive Quantization
49(4)
2.4.1 Forward Adaptive Quantization
50(1)
2.4.2 Backward Adaptive Quantization
51(1)
2.4.3 Adaptive Quantization with a One-Word Memory
52(1)
2.4.4 Switched Quantization
52(1)
2.5 PCM
53(3)
2.6 Summary
56(1)
Exercises
57(1)
References
57(2)
3 Differential Coding
59(22)
3.1 Introduction to DPCM
59(6)
3.1.1 Simple Pixel-to-Pixel DPCM
60(3)
3.1.2 General DPCM Systems
63(2)
3.2 Optimum Linear Prediction
65(2)
3.2.1 Formulation
65(1)
3.2.2 Orthogonality Condition and Minimum Mean Square Error
66(1)
3.2.3 Solution to Yule-Walker Equations
67(1)
3.3 Some Issues in the Implementation of DPCM
67(3)
3.3.1 Optimum DPCM System
67(1)
3.3.2 1-D, 2-D, and 3-D DPCM
67(2)
3.3.3 Order of Predictor
69(1)
3.3.4 Adaptive Prediction
69(1)
3.3.5 Effect of Transmission Errors
70(1)
3.4 Delta Modulation
70(4)
3.5 Interframe Differential Coding
74(3)
3.5.1 Conditional Replenishment
74(1)
3.5.2 3-D DPCM
75(1)
3.5.3 Motion-Compensated Predictive Coding
76(1)
3.6 Information-Preserving Differential Coding
77(1)
3.7 Summary
78(1)
Exercises
79(1)
References
79(2)
4 Transform Coding
81(36)
4.1 Introduction
81(6)
4.1.1 Hotelling Transform
81(2)
4.1.2 Statistical Interpretation
83(1)
4.1.3 Geometrical Interpretation
84(1)
4.1.4 Basis Vector Interpretation
85(1)
4.1.5 Procedures of Transform Coding
86(1)
4.2 Linear Transforms
87(5)
4.2.1 2-D Image Transformation Kernel
87(2)
4.2.1.1 Separability
87(1)
4.2.1.2 Symmetry
88(1)
4.2.1.3 Matrix Form
88(1)
4.2.1.4 Orthogonality
89(1)
4.2.2 Basis Image Interpretation
89(2)
4.2.3 Sub-image Size Selection
91(1)
4.3 Transforms of Particular Interest
92(10)
4.3.1 Discrete Fourier Transform
92(1)
4.3.2 Discrete Walsh Transform
93(1)
4.3.3 Discrete Hadamard Transform
94(2)
4.3.4 Discrete Cosine Transform
96(3)
4.3.4.1 Background
96(1)
4.3.4.2 Transformation Kernel
96(1)
4.3.4.3 Relationship with DFT
97(2)
4.3.5 Performance Comparison
99(3)
4.3.5.1 Energy Compaction
99(1)
4.3.5.2 Mean Square Reconstruction Error
100(2)
4.3.5.3 Computational Complexity
102(1)
4.3.5.4 Summary
102(1)
4.4 Bit Allocation
102(8)
4.4.1 Zonal Coding
103(1)
4.4.2 Threshold Coding
103(7)
4.4.2.1 Thresholding and Shifting
105(1)
4.4.2.2 Normalization and Roundoff
105(3)
4.4.2.3 Zigzag Scan
108(1)
4.4.2.4 Huffman Coding
108(2)
4.4.2.5 Special Codewords
110(1)
4.4.2.6 Rate Buffer Feedback and Equalization
110(1)
4.5 Some Issues
110(2)
4.5.1 Effect of Transmission Error
110(1)
4.5.2 Reconstruction Error Sources
110(1)
4.5.3 Comparison Between DPCM and TC
111(1)
4.5.4 Hybrid Coding
111(1)
4.6 Summary
112(2)
Exercises
114(1)
References
115(2)
5 Variable-Length Coding: Information Theory Results (II)
117(26)
5.1 Some Fundamental Results
117(7)
5.1.1 Coding an Information Source
117(2)
5.1.2 Some Desired Characteristics
119(3)
5.1.2.1 Block Code
119(1)
5.1.2.2 Uniquely Decodable Code
120(1)
5.1.2.3 Instantaneous Codes
121(1)
5.1.2.4 Compact Code
122(1)
5.1.3 Discrete Memoryless Sources
122(1)
5.1.4 Extensions of a Discrete Memoryless Source
122(2)
5.1.4.1 Definition
123(1)
5.1.4.2 Entropy
123(1)
5.1.4.3 Noiseless Source Coding Theorem
124(1)
5.2 Huffman Codes
124(4)
5.2.1 Required Rules for Optimum Instantaneous Codes
125(1)
5.2.2 Huffman Coding Algorithm
126(2)
5.2.2.1 Procedures
127(1)
5.2.2.2 Comments
127(1)
5.2.2.3 Applications
128(1)
5.3 Modified Huffman Codes
128(3)
5.3.1 Motivation
128(1)
5.3.2 Algorithm
129(1)
5.3.3 Codebook Memory Requirement
129(1)
5.3.4 Bounds on Average Codeword Length
130(1)
5.4 Arithmetic Codes
131(9)
5.4.1 Limitations of Huffman Coding
131(1)
5.4.2 The Principle of Arithmetic Coding
132(5)
5.4.2.1 Dividing Interval (0,1) into Subintervals
133(1)
5.4.2.2 Encoding
134(1)
5.4.2.3 Decoding
135(1)
5.4.2.4 Observations
136(1)
5.4.3 Implementation Issues
137(2)
5.4.3.1 Incremental Implementation
138(1)
5.4.3.2 Finite Precision
138(1)
5.4.3.3 Other Issues
138(1)
5.4.4 History
139(1)
5.4.5 Applications
139(1)
5.5 Summary
140(1)
Exercises
141(1)
References
142(1)
6 Run-Length and Dictionary Coding: Information Theory Results (III)
143(26)
6.1 Markov Source Model
143(3)
6.1.1 Discrete Markov Source
144(1)
6.1.2 Extensions of a Discrete Markov Source
145(1)
6.1.2.1 Definition
145(1)
6.1.2.2 Entropy
145(1)
6.1.3 Autoregressive Model
146(1)
6.2 Run-Length Coding
146(6)
6.2.1 1-D Run-Length Coding
147(1)
6.2.2 2-D Run-Length Coding
148(2)
6.2.2.1 Five Changing Pixels
149(1)
6.2.2.2 Three Coding Modes
150(1)
6.2.3 Effect of Transmission Error and Uncompressed Mode
150(3)
6.2.3.1 Error Effect in the 1-D RLC Case
151(1)
6.2.3.2 Error Effect in the 2-D RLC Case
151(1)
6.2.3.3 Uncompressed Mode
152(1)
6.3 Digital Facsimile Coding Standards
152(1)
6.4 Dictionary Coding
153(10)
6.4.1 Formulation of Dictionary Coding
153(1)
6.4.2 Categorization of Dictionary-Based Coding Techniques
153(1)
6.4.2.1 Static Dictionary Coding
153(1)
6.4.2.2 Adaptive Dictionary Coding
154(1)
6.4.3 Parsing Strategy
154(1)
6.4.4 Sliding Window (LZ77) Algorithms
155(4)
6.4.4.1 Introduction
155(1)
6.4.4.2 Encoding and Decoding
155(3)
6.4.4.3 Summary of the LZ77 Approach
158(1)
6.4.5 LZ78 Algorithms
159(4)
6.4.5.1 Introduction
159(1)
6.4.5.2 Encoding and Decoding
159(1)
6.4.5.3 LZW Algorithm
160(2)
6.4.5.4 Summary
162(1)
6.4.5.5 Applications
163(1)
6.5 International Standards for Lossless Still Image Compression
163(2)
6.5.1 Lossless Bilevel Still Image Compression
163(1)
6.5.1.1 Algorithms
163(1)
6.5.1.2 Performance Comparison
164(1)
6.5.2 Lossless Multilevel Still Image Compression
164(5)
6.5.2.1 Algorithms
164(1)
6.5.2.2 Performance Comparison
164(1)
6.6 Summary
165(1)
Exercises
166(1)
References
167(2)
7 Some Material Related to Multimedia Engineering
169(14)
7.1 Digital Watermarking
169(9)
7.1.1 Where to Embed Digital Watermark
169(1)
7.1.2 Watermark Signal with One Random Binary Sequence
170(3)
7.1.3 Challenge Faced by Digital Watermarking
173(2)
7.1.4 Watermark Embedded into the DC Component
175(3)
7.1.5 Digital Watermark with Multiple Information Bits and Error Correction Coding
178(1)
7.1.6 Conclusion
178(1)
7.2 Reversible Data Hiding
178(1)
7.3 Information Forensics
179(1)
References
179(4)
Part II Still Image Compression
8 Still Image Coding Standard-JPEG
183(14)
8.1 Introduction
183(2)
8.2 Sequential DCT-Based Encoding Algorithm
185(5)
8.3 Progressive DCT-Based Encoding Algorithm
190(2)
8.4 Lossless Coding Mode
192(1)
8.5 Hierarchical Coding Mode
193(1)
8.6 Summary
194(1)
Exercises
194(1)
References
195(2)
9 Wavelet Transform for Image Coding: JPEG2000
197(26)
9.1 A Review of Wavelet Transform
197(10)
9.1.1 Definition and Comparison with Short-Time Fourier Transform
197(4)
9.1.2 Discrete Wavelet Transform
201(2)
9.1.3 Lifting Scheme
203(4)
9.1.3.1 Three Steps in Forward Wavelet Transform
203(1)
9.1.3.2 Inverse Transform
204(1)
9.1.3.3 Lifting Version of CDF (2,2)
204(1)
9.1.3.4 A Numerical Example
205(1)
9.1.3.5 (5,3) Integer Wavelet Transform
206(1)
9.1.3.6 A Demonstration Example of (5,3) IWT
206(1)
9.1.3.7 Summary
207(1)
9.2 Digital Wavelet Transform for Image Compression
207(7)
9.2.1 Basic Concept of Image Wavelet Transform Coding
207(2)
9.2.2 Embedded Image Wavelet Transform Coding Algorithms
209(5)
9.2.2.1 Early Wavelet Image Coding Algorithms and Their Drawbacks
209(1)
9.2.2.2 Modern Wavelet Image Coding
210(1)
9.2.2.3 Embedded Zerotree Wavelet Coding
211(1)
9.2.2.4 Set Partitioning in Hierarchical Trees Coding
212(2)
9.3 Wavelet Transform for JPEG-2000
214(5)
9.3.1 Introduction of JPEG2000
214(2)
9.3.1.1 Requirements of JPEG-2000
214(1)
9.3.1.2 Parts of JPEG-2000
215(1)
9.3.2 Verification Model of JPEG2000
216(3)
9.3.3 An Example of Performance Comparison between JPEG and JPEG2000
219(1)
9.4 Summary
219(1)
Exercises
219(2)
References
221(2)
10 Non-standardized Still Image Coding
223(20)
10.1 Introduction
223(1)
10.2 Vector Quantization
224(8)
10.2.1 Basic Principle of Vector Quantization
224(3)
10.2.1.1 Vector Formation
225(1)
10.2.1.2 Training Set Generation
225(1)
10.2.1.3 Codebook Generation
226(1)
10.2.1.4 Quantization
226(1)
10.2.2 Several Image Coding Schemes with Vector Quantization
227(3)
10.2.2.1 Residual VQ
227(1)
10.2.2.2 Classified VQ
228(1)
10.2.2.3 Transform Domain VQ
228(1)
10.2.2.4 Predictive VQ
229(1)
10.2.2.5 Block Truncation Coding
229(1)
10.2.3 Lattice VQ for Image Coding
230(2)
10.3 Fractal Image Coding
232(4)
10.3.1 Mathematical Foundation
232(2)
10.3.2 IFS-Based Fractal Image Coding
234(2)
10.3.3 Other Fractal Image Coding Methods
236(1)
10.4 Model-Based Coding
236(1)
10.4.1 Basic Concept
236(1)
10.4.2 Image Modeling
236(1)
10.5 Summary
237(1)
Exercises
238(1)
References
238(5)
Part III Motion Estimation and Compensation
11 Motion Analysis and Motion Compensation
243(22)
11.1 Image Sequences
243(3)
11.2 Interframe Correlation
246(3)
11.3 Frame Replenishment
249(1)
11.4 Motion-Compensated Coding
250(3)
11.5 Motion Analysis
253(3)
11.5.1 Biological Vision Perspective
253(1)
11.5.2 Computer Vision Perspective
253(2)
11.5.3 Signal Processing Perspective
255(1)
11.6 Motion Compensation for Image Sequence Processing
256(3)
11.6.1 Motion-Compensated Interpolation
256(2)
11.6.2 Motion-Compensated Enhancement
258(1)
11.6.3 Motion-Compensated Restoration
259(1)
11.6.4 Motion-Compensated Down-Conversion
259(1)
11.7 Summary
259(2)
Exercises
261(1)
References
262(3)
12 Block Matching
265(34)
12.1 Non-overlapped, Equally Spaced, Fixed-Size, Small Rectangular Block Matching
265(2)
12.2 Matching Criteria
267(2)
12.3 Searching Procedures
269(12)
12.3.1 Full Search
269(1)
12.3.2 2-D Logarithm Search
269(1)
12.3.3 Coarse-Fine Three-Step Search
269(2)
12.3.4 Conjugate Direction Search
271(1)
12.3.5 Subsampling in the Correlation Window
272(1)
12.3.6 Multiresolution Block Matching
273(1)
12.3.7 Thresholding Multiresolution Block Matching
274(9)
12.3.7.1 Algorithm
275(1)
12.3.7.2 Threshold Determination
276(2)
12.3.7.3 Thresholding
278(1)
12.3.7.4 Experiments
279(2)
12.4 Matching Accuracy
281(1)
12.5 Limitations with Block-Matching Techniques
281(2)
12.6 New Improvements
283(10)
12.6.1 Hierarchical Block Matching
283(1)
12.6.2 Multigrid Block Matching
284(5)
12.6.2.1 Thresholding Multigrid Block Matching
285(3)
12.6.2.2 Optimal Multigrid Block Matching
288(1)
12.6.3 Predictive Motion Field Segmentation
289(3)
12.6.4 Overlapped Block Matching
292(1)
12.7 Summary
293(2)
Exercises
295(1)
References
296(3)
13 Pel-Recursive Technique
299(16)
13.1 Problem Formulation
299(2)
13.2 Descent Methods
301(7)
13.2.1 First-Order Necessary Conditions
301(1)
13.2.2 Second-Order Sufficient Conditions
301(1)
13.2.3 Underlying Strategy
302(1)
13.2.4 Convergence Speed
303(2)
13.2.4.1 Order of Convergence
304(1)
13.2.4.2 Linear Convergence
304(1)
13.2.5 Steepest Descent Method
305(1)
13.2.5.1 Formulae
305(1)
13.2.5.2 Convergence Speed
305(1)
13.2.5.3 Selection of Step Size
305(1)
13.2.6 Newton-Raphson's Method
306(2)
13.2.6.1 Formulae
306(1)
13.2.6.2 Convergence Speed
307(1)
13.2.6.3 Generalization and Improvements
307(1)
13.2.7 Other Methods
308(1)
13.3 Netravali-Robbins' Pel-Recursive Algorithm
308(2)
13.3.1 Inclusion of a Neighborhood Area
308(1)
13.3.2 Interpolation
309(1)
13.3.3 Simplification
309(1)
13.3.4 Performance
309(1)
13.4 Other Pel-Recursive Algorithms
310(1)
13.4.1 Bergmann's Algorithm (1982)
310(1)
13.4.2 Bergmann's Algorithm (1984)
310(1)
13.4.3 Cafforio and Rocca's Algorithm
310(1)
13.4.4 Walker and Rao's algorithm
311(1)
13.5 Performance Comparison
311(1)
13.6 Summary
312(1)
Exercises
313(1)
References
313(2)
14 Optical Flow
315(42)
14.1 Fundamentals
315(5)
14.1.1 2-D Motion and Optical Flow
316(1)
14.1.2 Aperture Problem
317(3)
14.1.3 Ill-Posed Problem
319(1)
14.1.4 Classification of Optical-Flow Techniques
319(1)
14.2 Gradient-Based Approach
320(8)
14.2.1 Horn and Schunck's Method
320(5)
14.2.1.1 Brightness Invariance Equation
320(2)
14.2.1.2 Smoothness Constraint
322(1)
14.2.1.3 Minimization
323(1)
14.2.1.4 Iterative Algorithm
323(2)
14.2.2 Modified Horn and Schunck Method
325(2)
14.2.3 Lucas and Kanade's Method
327(1)
14.2.4 Nagel's Method
327(1)
14.2.5 Uras, Girosi, Verri, and Torre's Method
327(1)
14.3 Correlation-Based Approach
328(18)
14.3.1 Anandan's Method
328(1)
14.3.2 Singh's Method
329(4)
14.3.2.1 Conservation Information
331(1)
14.3.2.2 Neighborhood Information
331(1)
14.3.2.3 Minimization and Iterative Algorithm
332(1)
14.3.3 Pan, Shi, and Shu's Method
333(13)
14.3.3.1 Proposed Framework
334(2)
14.3.3.2 Implementation and Experiments
336(9)
14.3.3.3 Discussion and Conclusion
345(1)
14.4 Multiple Attributes for Conservation Information
346(6)
14.4.1 Weng, Ahuja, and Huang's Method
347(1)
14.4.2 Xia and Shi's Method
347(10)
14.4.2.1 Multiple Image Attributes
348(1)
14.4.2.2 Conservation Stage
349(1)
14.4.2.3 Propagation Stage
350(1)
14.4.2.4 Outline of Algorithm
350(1)
14.4.2.5 Experimental Results
351(1)
14.4.2.6 Discussion and Conclusion
351(1)
14.5 Summary
352(2)
Exercises
354(1)
References
355(2)
15 Further Discussion and Summary on 2-D Motion Estimation
357(20)
15.1 General Characterization
357(3)
15.1.1 Aperture Problem
357(1)
15.1.2 Ill-Posed Inverse Problem
357(1)
15.1.3 Conservation Information and Neighborhood Information
358(1)
15.1.4 Occlusion and Disocclusion
358(1)
15.1.5 Rigid and Nonrigid Motion
359(1)
15.2 Different Classifications
360(7)
15.2.1 Deterministic Methods vs. Stochastic Methods
360(1)
15.2.2 Spatial Domain Methods vs. Frequency Domain Methods
360(4)
15.2.2.1 Optical-Flow Determination Using Gabor Energy Filters
361(3)
15.2.3 Region-Based Approaches vs. Gradient-Based Approaches
364(1)
15.2.4 Forward vs. Backward Motion Estimation
365(2)
15.3 Performance Comparison between Three Major Approaches
367(1)
15.3.1 Three Representatives
367(1)
15.3.2 Algorithm Parameters
367(1)
15.3.3 Experimental Results and Observations
367(1)
15.4 New Trends
368(3)
15.4.1 DCT-Based Motion Estimation
368(13)
15.4.1.1 DCT and DST Pseudophases
368(2)
15.4.1.2 Sinusoidal Orthogonal Principle
370(1)
15.4.1.3 Performance Comparison
371(1)
15.5 Summary
371(1)
Exercises
372(1)
References
372(5)
Part IV Video Compression
16 Fundamentals of Digital Video Coding
377(16)
16.1 Digital Video Representation
377(1)
16.2 Information Theory Results: Rate Distortion Function of Video Signal
378(3)
16.3 Digital Video Formats
381(4)
16.3.1 Digital Video Color Systems
381(2)
16.3.2 Progressive and Interlaced Video Signals
383(1)
16.3.3 Video Formats Used by Video Industry
383(2)
16.4 Current Status of Digital Video/Image Coding Standards
385(4)
16.5 Summary
389(1)
Exercises
389(2)
References
391(2)
17 Digital Video Coding Standards-MPEG-1/2 Video
393(40)
17.1 Introduction
393(1)
17.2 Features of MPEG-1/2 Video Coding
394(14)
17.2.1 MPEG-1 Features
394(8)
17.2.1.1 Introduction
394(1)
17.2.1.2 Layered Structure Based on Group of Pictures
394(1)
17.2.1.3 Encoder Structure
395(4)
17.2.1.4 Structure of the Compressed Bitstream
399(2)
17.2.1.5 Decoding Process
401(1)
17.2.2 MPEG-2 Enhancements
402(6)
17.2.2.1 Field/Frame-Prediction Mode
402(2)
17.2.2.2 Field/Frame DCT Coding Syntax
404(1)
17.2.2.3 Downloadable Quantization Matrix and Alternative Scan Order
404(1)
17.2.2.4 Pan and Scan
405(1)
17.2.2.5 Concealment Motion Vector
406(1)
17.2.2.6 Scalability
406(2)
17.3 MPEG-2 Video Encoding
408(5)
17.3.1 Introduction
408(1)
17.3.2 Pre-processing
408(1)
17.3.3 Motion Estimation and Motion Compensation
409(4)
17.3.3.1 Matching Criterion
410(1)
17.3.3.2 Searching Algorithm
410(2)
17.3.3.3 Advanced Motion Estimation
412(1)
17.4 Rate Control
413(4)
17.4.1 Introduction of Rate Control
413(1)
17.4.2 Rate Control of Test Model 5 for MPEG-2
413(4)
17.4.2.1 Step 1: Target Bit Allocation
413(1)
17.4.2.2 Step 2: Rate Control
414(2)
17.4.2.3 Step 3: Adaptive Quantization
416(1)
17.5 Optimum Mode Decision
417(7)
17.5.1 Problem Formation
417(3)
17.5.2 Procedure for Obtaining the Optimal Mode
420(3)
17.5.2.1 Optimal Solution
420(2)
17.5.2.2 Near-Optimal Greedy Solution
422(1)
17.5.3 Practical Solution with New Criteria for the Selection of Coding Mode
423(1)
17.6 Statistical Multiplexing Operations on Multiple Program Encoding
424(6)
17.6.1 Background of Statistical Multiplexing Operation
424(2)
17.6.2 VBR Encoders in StatMux
426(1)
17.6.3 Research Topics of StatMux
427(6)
17.6.3.1 Forward Analysis
428(1)
17.6.3.2 Potential Modeling Strategies and Methods
428(2)
17.7 Summary
430(1)
Exercises
430(1)
References
430(3)
18 Application Issues of MPEG-1/2 Video Coding
433(42)
18.1 Introduction
433(1)
18.2 ATSC DTV Standards
433(5)
18.2.1 A Brief History
433(2)
18.2.2 Technical Overview of ATSC Systems
435(3)
18.2.2.1 Picture Layer
435(1)
18.2.2.2 Compression Layer
436(1)
18.2.2.3 Transport Layer
437(1)
18.3 Transcoding with Bitstream Scaling
438(10)
18.3.1 Background
438(2)
18.3.2 Basic Principles of Bitstream Scaling
440(2)
18.3.3 Architectures of Bitstream Scaling
442(5)
18.3.3.1 Architecture 1: Cutting AC Coefficients
442(1)
18.3.3.2 Architecture 2: Increasing Quantization Step
443(1)
18.3.3.3 Architecture 3: Re-encoding with Old Motion Vectors and Old Decisions
444(1)
18.3.3.4 Architecture 4: Re-encoding with Old Motion Vectors and New Decisions
444(1)
18.3.3.5 Comparison of Bitstream Scaling Methods
445(2)
18.3.4 MPEG-2 to MPEG-4 Transcoding
447(1)
18.4 Down-Conversion Decoder
448(12)
18.4.1 Background
448(2)
18.4.2 Frequency Synthesis Down-Conversion
450(2)
18.4.3 Low-Resolution Motion Compensation
452(2)
18.4.4 Three-Layer Scalable Decoder
454(3)
18.4.5 Summary of Down-Conversion Decoder
457(1)
Appendix A: DCT-to-Spatial Transformation
458(1)
Appendix B: Full-Resolution Motion Compensation in Matrix Form
459(1)
18.5 Error Concealment
460(11)
18.5.1 Background
460(2)
18.5.2 Error Concealment Algorithms
462(5)
18.5.2.1 Codeword Domain Error Concealment
463(1)
18.5.2.2 Spatio-temporal Error Concealment
463(4)
18.5.3 Algorithm Enhancements
467(3)
18.5.3.1 Directional Interpolation
467(1)
18.5.3.2 I-picture Motion Vectors
468(1)
18.5.3.3 Spatial Scalable Error Concealment
469(1)
18.5.4 Summary of Error Concealment
470(1)
18.6 Summary
471(1)
Exercises
471(1)
References
472(3)
19 MPEG-4 Video Standard: Content-Based Video Coding
475(30)
19.1 Introduction
475(1)
19.2 MPEG-4 Requirements and Functionalities
476(2)
19.2.1 Content-Based Interactivity
476(1)
19.2.1.1 Content-Based Manipulation and Bitstream Editing
476(1)
19.2.1.2 Synthetic and Natural Hybrid Coding
476(1)
19.2.1.3 Improved Temporal Random Access
476(1)
19.2.2 Content-Based Efficient Compression
477(1)
19.2.2.1 Improved Coding Efficiency
477(1)
19.2.2.2 Coding of Multiple Concurrent Data Streams
477(1)
19.2.3 Universal Access
477(1)
19.2.3.1 Robustness in Error-Prone Environments
477(1)
19.2.3.2 Content-Based Scalability
477(1)
19.2.4 Summary of MPEG-4 Features
477(1)
19.3 Technical Description of MPEG-4 Video
478(16)
19.3.1 Overview of MPEG-4 Video
478(1)
19.3.2 Motion Estimation and Compensation
479(2)
19.3.2.1 Adaptive Selection of 16 x 16 Block or Four 8 x 8 Blocks
480(1)
19.3.2.2 Overlapped Motion Compensation
481(1)
19.3.3 Texture Coding
481(5)
19.3.3.1 INTRA DC and AC Prediction
482(1)
19.3.3.2 Motion Estimation/Compensation of Arbitrary-Shaped VOP
483(1)
19.3.3.3 Texture Coding of Arbitrary-Shaped VOP
484(2)
19.3.4 Shape Coding
486(3)
19.3.4.1 Binary Shape Coding with CAE Algorithm
486(2)
19.3.4.2 Gray-Scale Shape Coding
488(1)
19.3.5 Sprite Coding
489(1)
19.3.6 Interlaced Video Coding
490(1)
19.3.7 Wavelet-Based Texture Coding
490(1)
19.3.7.1 Decomposition of the Texture Information
490(1)
19.3.7.2 Quantization of Wavelet Coefficients
491(1)
19.3.7.3 Coding of Wavelet Coefficients of Low-Low Band and Other Bands
491(1)
19.3.7.4 Adaptive Arithmetic Coder
491(1)
19.3.8 Generalized Spatial and Temporal Scalability
491(2)
19.3.9 Error Resilience
493(1)
19.4 MPEG-4 Visual Bitstream Syntax and Semantics
494(1)
19.5 MPEG-4 Visual Profiles and Levels
495(1)
19.6 MPEG-4 Video Verification Model
496(6)
19.6.1 VOP-Based Encoding and Decoding Process
497(1)
19.6.2 Video Encoder
497(4)
19.6.2.1 Video Segmentation
497(2)
19.6.2.2 Intra/Inter Mode Decision
499(1)
19.6.2.3 Off-line Sprite Generation
499(1)
19.6.2.4 Multiple VO Rate Control
500(1)
19.6.3 Video Decoder
501(1)
19.7 Summary
502(1)
Exercises
502(1)
References
503(2)
20 ITU-T Video Coding Standards H.261 and H.263
505(22)
20.1 Introduction
505(1)
20.2 H.261 Video Coding Standard
505(5)
20.2.1 Overview of H.261 Video Coding Standard
505(2)
20.2.2 Technical Detail of H.261
507(1)
20.2.3 Syntax Description
508(2)
20.2.3.1 Picture Layer
508(1)
20.2.3.2 Group of Blocks Layer
508(1)
20.2.3.3 Macroblock Layer
508(1)
20.2.3.4 Block Layer
509(1)
20.3 H.263 Video Coding Standard
510(6)
20.3.1 Overview of H.263 Video Coding
510(1)
20.3.2 Technical Features of H.263
511(5)
20.3.2.1 Half-Pixel Accuracy
511(1)
20.3.2.2 Unrestricted-Motion Vector Mode
512(1)
20.3.2.3 Advanced-Prediction Mode
512(2)
20.3.2.4 Syntax-Based Arithmetic Coding
514(1)
20.3.2.5 PB-frames
515(1)
20.4 H.263 Video Coding Standard Version 2
516(8)
20.4.1 Overview of H.263 Version 2
516(1)
20.4.2 New Features of H.263 Version 2
516(15)
20.4.2.1 Scalability
516(2)
20.4.2.2 Improved PB-frames
518(1)
20.4.2.3 Advanced Intra Coding
518(1)
20.4.2.4 Deblocking Filter
519(1)
20.4.2.5 Slice-Structured Mode
520(1)
20.4.2.6 Reference Picture Selection
521(1)
20.4.2.7 Independent Segmentation Decoding
521(1)
20.4.2.8 Reference Picture Resampling
521(1)
20.4.2.9 Reduced-Resolution Update
522(1)
20.4.2.10 Alternative INTER VLC (AIV) and Modified Quantization
523(1)
20.4.2.11 Supplemental Enhancement Information
524(1)
20.5 H.263++ Video Coding and H.26L
524(1)
20.6 Summary
525(1)
Exercises
525(1)
References
525(2)
21 Video Coding Standard-H.264/AVC
527(26)
21.1 Introduction
527(1)
21.2 Overview of the H.264/AVC Codec Structure
528(3)
21.3 Technical Description of H.264/AVC Coding Tools
531(15)
21.3.1 Instantaneous Decoding Refresh Picture
531(1)
21.3.2 Switching I Slices and Switching P Slices
532(2)
21.3.3 Transform and Quantization
534(2)
21.3.4 Intra Frame Coding with Directional Spatial Prediction
536(1)
21.3.5 Adaptive Block Size Motion Compensation
536(1)
21.3.6 Motion Compensation with Multiple References
537(1)
21.3.7 Entropy Coding
538(5)
21.3.8 Loop Filter
543(2)
21.3.9 Error Resilience Tools
545(1)
21.4 Profiles and Levels of H.264/AVC
546(4)
21.4.1 Profiles of H.264/AVC
547(1)
21.4.2 Levels of H.264/AVC
548(2)
21.5 Summary
550(1)
Exercises
550(1)
References
550(3)
22 A New Video Coding Standard-HEVC/H.265
553(26)
22.1 Introduction
553(1)
22.2 Overview of HEVC/H.265 Codec Structure
554(1)
22.3 Technical Description of H.265/HEVC Coding Tools
555(13)
22.3.1 Video Coding Block Structure (Codesequois 2012)
555(4)
22.3.2 Predictive Coding Structure
559(3)
22.3.3 Transform and Quantization
562(1)
22.3.4 Loop Filters
563(3)
22.3.5 Entropy Coding
566(1)
22.3.6 Parallel Processing Tools
567(1)
22.4 HEVC/H.265 Profiles and Range Extensions (Sullivan et al. 2013)
568(6)
22.4.1 Version 1 of HEVC/H.265
568(1)
22.4.2 Version 2 of HEVC/H.265
569(3)
22.4.3 Versions 3 and 4 of HEVC/H.265
572(2)
22.5 Performance Comparison with H.264/AVC
574(3)
22.5.1 Technical Difference Between H.264/AVC and HEVC/H.265
574(1)
22.5.2 Performance Comparison Between H.264/AVC and HEVC/H.265
575(2)
22.6 Summary
577(1)
Exercises
577(1)
References
577(2)
23 Internet Video Coding Standard-IVC
579(12)
23.1 Introduction
579(2)
23.2 Coding Structure of IVC Standard
581(5)
23.2.1 Adaptive Transform
582(1)
23.2.2 Intra Prediction
582(1)
23.2.3 Inter Prediction
582(1)
23.2.4 Motion Vector Prediction
583(1)
23.2.5 Sub-pel Interpolation
584(1)
23.2.6 Reference Frames
584(1)
23.2.7 Entropy Coding
585(1)
23.2.8 Loop Filtering
585(1)
23.3 Performance Evaluation
586(3)
23.4 Summary
589(1)
Exercises
589(1)
References
589(2)
24 MPEG Media Transport
591(32)
24.1 Introduction
591(1)
24.2 MPEG-2 System
592(13)
24.2.1 Major Technical Definitions in MPEG-2 System Document
593(1)
24.2.2 Transport Streams
594(5)
24.2.2.1 Structure of Transport Streams
595(2)
24.2.2.2 Transport Stream Syntax
597(2)
24.2.3 Transport Streams Splicing
599(2)
24.2.4 Program Streams
601(2)
24.2.5 Timing Model and Synchronization
603(2)
24.3 MPEG-4 System
605(5)
24.3.1 Overview and Architecture
605(3)
24.3.2 Systems Decoder Model
608(1)
24.3.3 Scene Description
609(1)
24.3.4 Object Description Framework
609(1)
24.4 MMT
610(6)
24.4.1 Overview
610(2)
24.4.2 MMT Content Model
612(1)
24.4.3 Encapsulation of MPU
613(1)
24.4.4 Packetized Delivery of Package
614(1)
24.4.5 Cross Layer Interface
615(1)
24.4.6 Signaling
615(1)
24.4.7 Hypothetical Receiver Buffer Model
616(1)
24.5 Dynamic Adaptive Streaming over HTTP
616(4)
24.5.1 Introduction
617(1)
24.5.2 Media Presentation Description
618(1)
24.5.3 Segment Format
619(1)
24.6 Summary
620(1)
Exercises
620(1)
References
621(2)
Index 623
Huifang Sun received the B.S. degree in Electrical Engineering from Harbin Engineering Institute (Harbin Engineering University now), Harbin, China in 1967, and the Ph.D. degree in Electrical Engineering from University of Ottawa, Ottawa, Canada. In 1986 he jointed Fairleigh Dickinson University, Teaneck, New Jersey, as an Assistant Professor and promoted to an Associate Professor in 1990. From 1990 to 1995 he was with the David Sarnoff Research Center (Sarnoff Corp), Princeton, New Jersey, as a member of technical staff and later promoted to Technology Leader of Digital Video Technology. He joined Mitsubishi Electric Research Laboratories (MERL), in 1995 as a Senior Principal Technical Staff and was promoted as Deputy Director in 1997, Vice President and MERL Fellow in 2003 and now as MERL Fellow. He holds 66 U.S. patents and has authored or co-authored 2 books as well as more than 150 journal and conference papers. For his contributions on HDTV development he obtained 1994 Sarnoff technical achievement award. He also obtained the best paper award of IEEE Transactions on Consumer Electronics in 1993, the best paper award of International Conference on Consumer Electronics in 1997 and the best paper award of IEEE Transaction on CSVT in 2003. He was an Associate Editor for IEEE Transaction on Circuits and Systems for Video Technology and the Chair of Visual Processing Technical Committee of IEEE Circuits and System Society. He is an IEEE Life Fellow. He also served as a guest professor of Peking University, Tianjin University, Shanghai Jiaotong University (Guest Researcher) and several other universities in China.

Dr. Yun Qing Shi has been a professor with the Department of Electrical and Computer Engineering at the New Jersey Institute of Technology (NJIT), Newark, NJ since 1987. He has authored and co-authored more than 300 papers in his research areas, a book on Image and Video Compression, three book chapters on Image Data Hiding, one book chapter on Steganalysis, and one book chapter on Digital Image Processing. He has edited more than 10 proceedings of international workshops and conferences, holds 29 awarded US patents, and delivered more than 120 invited talks around the world. He is a member of IEEE Circuits and Systems Society (CASS)'s Technical Committee of Visual Signal Processing and Communications, Technical Committee of Multimedia Systems and Applications, an associate editor of IEEE Transactions on Information Forensics and Security, and a fellow of IEEE for his contribution to Multidimensional Signal Processing since 2005.