Lossless Medical Image Compression using Redundancy Analysis

We studied two image characteristics, the smoothness and the similarity, which give rise to local and global redundancy in image representation. The smoothness means that the gray level values within a given block vary gradually rather than abruptly. The similarity means that any patterns in an image repeat itself anywhere in the rest of the image. In this sense, we proposed a lossless medical image compression scheme which exploits both types of redundancy. The proposed method segments the image into variable block size(VBS) and encodes them depending on characteristics of the blocks. The proposed compression schemes works better 10~40[%] than other compression scheme such as the Huffman, the arithmetic, the Lempel-Ziv, HINT(Hierarchical Interpolation), JPEG-LS(Lossless Scheme of JPEG) and lossless JPEG2000.