Subband adaptive dictionaries for wavelet/matching pursuits image coding

Reference:

Monro, D., Huo, W. and Wang, X., 2006. Subband adaptive dictionaries for wavelet/matching pursuits image coding. In: 2006 International Conference on Image Processing. Piscataway, NJ: IEEE Computer Society, pp. 2133-2136.

Related documents:

Official URL:

http://dx.doi.org/10.1109/ICIP.2006.312830

Abstract

Different dictionaries of basis functions are applied to the four types of sub-bands in coding a wavelet decomposed image by matching pursuits. A dictionary of 2D bases is formed separably from a set of previously determined 1D bases. Four masks are defined which select different subsets of the dictionary for coding LL, HL, LH and HH sub-bands. Masks are found by progressively searching for bases which give the highest PSNR at a desired bit rate. It is found that the PSNR of a compressed image increases rapidly at first as bases are added to the masks. It then declines and oscillates. Over a range of small numbers of bases for any bit rate the PSNR is better than with the full codebook. Using sparse dictionaries adapted to different sub-bands gives low computational cost while maintaining high quality, but shows dependency on the bit rate and the image

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