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-b
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.
- © Elsevier Science 1994
- 24th November 1994
- Elsevier Science
- eBook ISBN:
- Hardcover ISBN:
University of Nice-Sophia Antipolis, Valbonne, France