Subband adaptive dictionaries for wavelet/matching pursuits image coding

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 I D 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.