Description The rapid advancements in image communication technologies are documented in the book series, “Advances in Image Communication”.
Each publication provides an in-depth exploration of an intrinsic element of the multi-disciplinary field and together they form a comprehensive
overview of the whole.
This volume, the fifth in the series, examines the definition, study and use of the wavelet transform in communications
for two-dimensional (2-D) digital signals. The transform is used for signal reorganization before compression and the trade-off between
these two steps and the whole compression process is discussed.
The five chapters specifically present the theory of wavelets applied
to images, then applications of compression of still images and sequences. Chapter 1 introduces biorthogonal bases of compactly supported
wavelets: this generalization of orthonormal wavelet theory allows the use of linear phase filters. A non rectangular wavelet representation
of 2-D signals is developed in the second chapter: the properties usually used with wavelets, phase, linearity, and regularity are discussed.
Chapter 3 is composed of three parts: a description of commonly used biorthogonal wavelets; a presentation of vector quantization algorithms;
a consideration of lattice vector quantization followed by a discussion of the bit allocation procedure (with experimental results given).
The fourth chapter deals with a region-based discrete wavelet transform for image coding. Chapter 5 investigates the transmission of
image sequences: wavelet transforms and motion estimation are detailed in a multiconstraint approach of image sequence coding.
Contents
Biorthogonal Wavelets and Dual Filters (A. Cohen). Abstract. Introduction. The Construction of Biorthogonal Wavelets.
Examples in 1-D. Biorthogonal splines. The Burt-Adelson wavelets. Optimizing the dual filter design. Examples in 2-D. The quincunx sublattice
construction. The hexagonal construction. Conclusion. References.
Non Rectangular Wavelet Representation of 2-D Signals. Application
to Image Coding (C. Guillemot, A. Enis Cetin, R. Ansari). Abstract. Introduction. Nonrectangular Wavelet Representation of 2-D
Signals. Nonseparable 2-D wavelets. Nonrectangular multiresolution representation. Construction of Bases for the Representation of Quincunx-Sampled
Signals. 1-D wavelet construction using Lagrange halfband filters. Construction of nonrectangular 2-D orthogonal bases. Construction
of biorthogonal bases. Application to Image Coding. Summary. References.
Wavelet Transform and Image Coding (M. Antonini,
T. Gaidon, P. Mathieu, M. Barlaud). Abstract. Wavelet Transform. Introduction. Definition of wavelets. Multiresolution analysis - scaling
function. Multiresolution analysis and digital filter banks. Quality criteria for wavelets used in image processing. Biorthogonal wavelets.
Extension to the bidimensional case. Statistical properties of wavelets coefficients. Conclusion. Appendix A. Bibliography. Vector Quantization.
Introduction. Quantization. Codebook entropy. Vector quantization versus scalar quantization. Codebook design. Lattice Vector Quantization
(LVQ). Bit allocation procedure. Experimental Results. Introduction. Lattice vector quantizer design. Coding under psychovisual considerations.
Dyadic or quincunx scheme for coding? Appendix B. Bibliography. Conclusion. Acknowledgments.
A Region-Based Discrete Wavelet
Transform (RBDWT) for Image Coding (H.J. Barnard, J.H. Weber, J. Biemond). Abstract. Introduction. The discrete wavelet transform.
Region-based coding. Principle of the region-based discrete wavelet transform. Scope and organization. The Implementation of the RBDWT.
Decomposition of the segmentation mask. Filtering and downsampling with the RBDWT. The Coding Scheme. The segmentation. The bit allocation.
The quantization. Comparison to the Standard DWT Coding Scheme. Theoretical advantages and disadvantages of the RBDWT coding scheme.
Experimental comparison of the RBDWT and the standard DWT coding schemes. Multiresolution coding of images using the RBDWT. Application
to video coding. Conclusions and Further Research. Bibliography.
Wavelet Transform and Motion Estimation for Image Sequence Coding:
A Multiconstraint Approach (N. Baaziz, C. Labit). Abstract. Introduction. Multiresolution Representations of Image Sequences.
A generalized typology of multiresolution decompositions. Comparison based on local and global subband entropies. Discussion. Monoresolution
Motion Estimation Framework. Adaptive pel-recursive motion estimation algorithm. Wiener-based algorithm. Modified Wiener-based approach.
Multiresolution Motion Estimation. Problem statement. Multigrid Walker-Rao algorithm on wavelet pyramids. Multiconstraint Algorithm.
Discussion. References.
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