AN IMAGE MULTIRESOLUTION REPRESENTATION FOR LOSSLESS AND LOSSY COMPRESSION

We propose a new image multiresolution transform that is suited for bo th lossless (reversible) and lossy compression. The new transformation is similar to the subband decomposition, but can be computed with onl y integer addition and bit-shift operations. During its calculation, t he number of bits required to represent the transformed image is kept small through careful scaling and truncations. Numerical results show that the entropy obtained with the new transform is smaller than that obtained with predictive coding of similar complexity. In addition, we propose entropy-coding methods that exploit the multiresolution struc ture, and can efficiently compress the transformed image for progressi ve transmission (up to exact recovery). The lossless compression ratio s are among the best in the literature, and simultaneously the rate ve rsus distortion performance is comparable to those of the most efficie nt lossy compression methods.