Rank-order polynomial subband decomposition for medical image compression

In this paper, the problem of progressive lossless image coding is addresse d, A nonlinear decomposition for progressive lossless compression is presen ted. The decomposition into subbands is called rank-order polynomial decomp osition (ROPD) according to the polynomial prediction models used. The deco mposition method presented here is a further development and generalization of the morphological subband decomposition (MSD) introduced earlier by the same research group. It is shown that ROPD provides similar or slightly be tter results than the compared coding schemes such as the codec based on se t partitioning in hierarchical trees (SPIHT) and the codec based on wavelet /trellis-coded quantization (WTCQ). Our proposed method highly outperforms the standard JPEG. The proposed lossless compression scheme has the functio nality of having a completely embedded bit stream, which allows for data br owsing. It is shown that the ROPD has a better lossless rate than the MSD b ut it has also a much better browsing quality when only a part of the bit s tream is decompressed. Finally, the possibility of hybrid lossy/lossless co mpression is presented using ultrasound images. As with other compression a lgorithms, considerable gain can be obtained if only the regions of interes t are compressed losslessly.