Application of compactly supported wavelets to image compression

William R. Zettler; John C. Huffman; David C. P. Linden

doi:10.1117/12.19505

1 June 1990 Application of compactly supported wavelets to image compression

William R. Zettler, John C. Huffman, David C. P. Linden

Proceedings Volume 1244, Image Processing Algorithms and Techniques; (1990) https://doi.org/10.1117/12.19505
Event: Electronic Imaging: Advanced Devices and Systems, 1990, Santa Clara, CA, United States

Abstract

Multilevel unitary wavelet transform methods for image compression are described. The sub-band decomposition preserves geometric image structure within each sub-band or level. This yields a multilevel image representation. The use of orthonormal bases of compactly supported wavelets to represent a discrete signal in 2 dimensions yields a localized representation of coefficient energy. Subsequent coding of the multiresolution representation is achieved through techniques such as scalar/vector quantization, hierarchical quantization, entropy coding, and non-linear prediction to achieve compression. Performance advantages over the Discrete Cosine Transform are discussed. These include reduction of errors and artifacts typical of Fourier-based spectral methods, such as frequency-domain quantization noise and the Gibbs phenomenon. The wavelet method also eliminates distortion arising from data blocking. The paper includes a quick review of past/present compression techniques, with special attention paid to the Haar transfOrm, the simplest wavelet transform, and conventional Fourier-based subband coding. Computational results are presented.

Citation Download Citation

William R. Zettler, John C. Huffman, and David C. P. Linden "Application of compactly supported wavelets to image compression", Proc. SPIE 1244, Image Processing Algorithms and Techniques, (1 June 1990); https://doi.org/10.1117/12.19505

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