Image compression using subband/wavelet transform and adaptive multiple-distribution entropy coding

摘要

Image compression methods using subband/wavelet transform and adaptive multiple distribution entropy coding (AMDEC) are presented. The methods are suitable for the coding of still images, as well as, motion compensated prediction error images for video compression. First, the subband/wavelet transform coefficients are uniformly quantized. For still image coding perception based weight quantization is used. Space filling scanning, subband partitioning and classification methods are used in dividing the original source of quantized coefficients into a number of subsources with corresponding distributions. A hierarchical partition priority coding (PPC) approach is followed, that is, given a suitable partitioning of their range, the transform coefficients are ordered based on their magnitude. AMDEC is applied to the output of PPC, which contains magnitude and location information, using adaptive arithmetic coding based on the histograms of the various subsources. Experimental results on standard monochromatic images and video-conference image sequences demonstrate the great performance of the proposed AMDEC methods.