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Wavelet filter evaluation for image compression
Choice of filter bank in wavelet compression is a critical issue that affects image quality as well as system design. Although regularity is sometimes used in filter evaluation, its success at predicting compression performance is only partial. A more reliable evaluation can be obtained by consideri...
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Published in: | IEEE transactions on image processing 1995-08, Vol.4 (8), p.1053-1060 |
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container_title | IEEE transactions on image processing |
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creator | Villasenor, J.D. Belzer, B. Liao, J. |
description | Choice of filter bank in wavelet compression is a critical issue that affects image quality as well as system design. Although regularity is sometimes used in filter evaluation, its success at predicting compression performance is only partial. A more reliable evaluation can be obtained by considering an L-level synthesis/analysis system as a single-input, single-output, linear shift-variant system with a response that varies according to the input location module (2/sup L/,2/sup L/). By characterizing a filter bank according to its impulse response and step response in addition to regularity, we obtain reliable and relevant (for image coding) filter evaluation metrics. Using this approach, we have evaluated all possible reasonably short (less than 36 taps in the synthesis/analysis pair) minimum-order biorthogonal wavelet filter banks. Of this group of over 4300 candidate filter banks, we have selected and present here the filters best suited to image compression. While some of these filters have been published previously, others are new and have properties that make them attractive in system design.< > |
doi_str_mv | 10.1109/83.403412 |
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Although regularity is sometimes used in filter evaluation, its success at predicting compression performance is only partial. A more reliable evaluation can be obtained by considering an L-level synthesis/analysis system as a single-input, single-output, linear shift-variant system with a response that varies according to the input location module (2/sup L/,2/sup L/). By characterizing a filter bank according to its impulse response and step response in addition to regularity, we obtain reliable and relevant (for image coding) filter evaluation metrics. Using this approach, we have evaluated all possible reasonably short (less than 36 taps in the synthesis/analysis pair) minimum-order biorthogonal wavelet filter banks. Of this group of over 4300 candidate filter banks, we have selected and present here the filters best suited to image compression. 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Although regularity is sometimes used in filter evaluation, its success at predicting compression performance is only partial. A more reliable evaluation can be obtained by considering an L-level synthesis/analysis system as a single-input, single-output, linear shift-variant system with a response that varies according to the input location module (2/sup L/,2/sup L/). By characterizing a filter bank according to its impulse response and step response in addition to regularity, we obtain reliable and relevant (for image coding) filter evaluation metrics. Using this approach, we have evaluated all possible reasonably short (less than 36 taps in the synthesis/analysis pair) minimum-order biorthogonal wavelet filter banks. Of this group of over 4300 candidate filter banks, we have selected and present here the filters best suited to image compression. While some of these filters have been published previously, others are new and have properties that make them attractive in system design.< ></abstract><cop>New York, NY</cop><pub>IEEE</pub><pmid>18291999</pmid><doi>10.1109/83.403412</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
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ispartof | IEEE transactions on image processing, 1995-08, Vol.4 (8), p.1053-1060 |
issn | 1057-7149 1941-0042 |
language | eng |
recordid | cdi_pubmed_primary_18291999 |
source | IEEE Electronic Library (IEL) Journals |
subjects | Applied sciences Continuous wavelet transforms Exact sciences and technology Filter bank Finite impulse response filter Image coding Image processing Image quality Image reconstruction Information, signal and communications theory Nonlinear filters Signal processing Signal resolution Telecommunications and information theory Wavelet transforms |
title | Wavelet filter evaluation for image compression |
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