Wavelets in Image Communication
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Overview
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.
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