Medical image compression algorithms are now essential to database access, storage, and transmission. This study presents a hybrid approach to mammogram image compression using optimal wavelet sub-band filters. The mammogram image is first morphologically segmented into two regions, Region of Interest, ROI, and Background, BG. The two sub-images are encoded using a hybrid, lossless and lossy, method. Huffman and Differential Huffman Encoding are used for the lossless compression. A wavelet packet containing a total of sixty wavelets from four different wavelet families is used for the lossy compression encoding. A total of fifty four 8-bit grey scale mammograms were used in the testing and analysis of this study.; The overall performance of the algorithm is evaluated using widely acceptable subjective and objective criteria. Furthermore, established methods such as a 8x8 DCT, DFT, and a modified JPEG2000 are used for comparison purposes.; The overall performance, in terms of compression rate, of the proposed algorithm was in one case similar to most current methods, and significantly better in the second case. The compressed image reproduced the original image by 100% in the ROI and above 95% in the BG region.
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