Progressive image transmission : the role of rationality, cooperation, and justice

The authors present a sound, practical approach to information prioritization in progressive image transmission. The method, suitable for a variety of imaging applications from consumer products to the defense, publishing, science, and law enforcement industries, first states some general principles that the solution must obey and then derives the solution that satisfies exactly those principles. The text is intended for graduate students as well as engineers and research scientists in the field of image coding.

Preface	p. ix
Chapter 1 Rationality in Progressive Transmission	p. 1
1.1 Introduction	p. 1
1.2 Basic elements of the selection problem	p. 4
1.3 Basic axioms for avoiding forms of behavioral inconsistency	p. 5
1.4 Progressive transmission utility functions	p. 8
1.4.1 Rate control procedure	p. 13
Chapter 2 Coder Evaluation Procedure	p. 15
2.1 Introduction	p. 15
2.2 Compound gain: A computational tool for predicting visual distinctness	p. 17
2.3 Comparison between PSNR and CG	p. 19
2.3.1 Images	p. 20
2.3.2 Psychophysical target distinctness	p. 22
2.3.3 Evaluation function	p. 24
2.3.4 Experiment 1	p. 25
2.3.5 Experiment 2	p. 26
2.3.6 Statistical accuracy	p. 26
2.4 Objective coder selection procedure	p. 28
2.4.1 An example	p. 29
2.5 Assessment of risk attitudes in rational transmission	p. 31
2.5.1 Objective evaluation	p. 37
2.5.2 Subjective evaluation	p. 37
Chapter 3 Visual Distinctness of Prioritized Data	p. 41
3.1 Introduction	p. 41
3.2 Prioritization by distortion measures and by human observers	p. 44
3.2.1 Distortion measures for prioritization protocols	p. 44
3.2.2 Psychophysical experiments	p. 47
3.3 Results and discussion	p. 49
3.3.1 Experiment 1	p. 49
3.3.2 Experiment 2	p. 51
3.3.3 Experiment 3	p. 52
3.3.4 Experiment 4	p. 54
Chapter 4 Integration of Rationality and Cooperation	p. 61
4.1 Introduction	p. 61
4.2 Cooperative decision for bit allocation	p. 62
4.3 Self-control of risk aversion attitude in progressive transmission	p. 63
4.4 Integration of rationality/cooperation in unsteady-state transmission	p. 65
4.4.1 Self-rewarding risk attitude	p. 67
4.4.2 Self-rewarding attitude integrates cooperative action with rationality	p. 68
4.5 Experimental results	p. 70
4.5.1 Subjective coder evaluation	p. 70
4.5.2 Objective coder evaluation	p. 72
Chapter 5 Conflict and Cooperation at Very Low Bit Rates	p. 81
5.1 Introduction	p. 81
5.2 Acceleration of benefit gain by increasing risk attitude tolerance	p. 82
5.3 A coalitional game for controlling a quantizer's risk tolerance	p. 84
5.4 A family of solutions for the coalitional game	p. 86
5.5 Assessment of weight functions	p. 88
5.6 Experimental results	p. 91
5.6.1 Subjective coder evaluation	p. 91
5.6.2 Objective coder evaluation	p. 96
5.7 The self-rewarding solution and the dissatisfaction solution	p. 99
5.7.1 Basic properties of the dissatisfaction solution	p. 99
5.7.2 Relationship between the self-rewarding solution and the dissatisfaction solution	p. 100
Chapter 6 Justice in Rational Transmission	p. 105
6.1 Introduction	p. 105
6.2 Just quantizer formation	p. 110
6.3 A priori importance of an SOT	p. 112
6.3.1 SOT-restricted games: Cooperation and communication among wavelet coefficients	p. 113
6.3.2 Zerotree solution for SOT-restricted games	p. 114
6.4 Experimental results	p. 117
6.4.1 Subjective coder evaluation	p. 117
6.4.2 Objective coder evaluation	p. 122
6.5 Just transmission	p. 125
Epilogue: Rationality, Cooperation, and Justice	p. 129
Appendix A Fundamentals in Embedded Zerotree Wavelet Coding	p. 143
A.1 Introduction	p. 143
A.2 Progressive transmission	p. 144
A.3 Wavelet transform; decomposition into subbands	p. 146
A.4 Compression algorithm based on "zerotrees"	p. 151
A.4.1 SPIHT	p. 153
Appendix B REWIC Algorithm	p. 163
B.1 Algorithms for encoding/decoding an image in REWIC format	p. 163
B.2 Algorithms for encoding/decoding an image in RECON format	p. 168
Appendix C Information Theoretic Measure	p. 173
C.1 Introduction	p. 173
C.2 Information conservation constraint	p. 178
C.2.1 Selective information gain	p. 180
C.2.2 Properties of the selective information gain	p. 180
C.3 Significance conservation constraint	p. 183
C.3.1 Compound information gain	p. 183
C.3.2 Properties of the CG	p. 185
Appendix D Best Achievable Compression Ratio	p. 189
D.1 Introduction	p. 189
D.2 The best achievable compression ratio	p. 190
D.3 Effects of lossy compression at the best achievable compression ratio	p. 193
D.3.1 Results	p. 195
Bibliography	p. 199
Index	p. 209

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