Wavelet filter evaluation for image compression
- 1 January 1995
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Image Processing
- Vol. 4 (8) , 1053-1060
- https://doi.org/10.1109/83.403412
Abstract
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(L),2(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.Keywords
This publication has 15 references indexed in Scilit:
- An embedded hierarchical image coder using zerotrees of wavelet coefficientsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- A filter based bit allocation scheme for subband compression of HDTVIEEE Transactions on Image Processing, 1992
- Biorthogonal bases of compactly supported waveletsCommunications on Pure and Applied Mathematics, 1992
- Image coding using wavelet transformIEEE Transactions on Image Processing, 1992
- Shiftable multiscale transformsIEEE Transactions on Information Theory, 1992
- Entropy-based algorithms for best basis selectionIEEE Transactions on Information Theory, 1992
- Signal-adapted multiresolution transform for image codingIEEE Transactions on Information Theory, 1992
- Vector quantization for entropy coding of image subbandsIEEE Transactions on Image Processing, 1992
- Wavelets and Dilation Equations: A Brief IntroductionSIAM Review, 1989
- A theory for multiresolution signal decomposition: the wavelet representationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1989