Min-max compression methods for medical image databases
ACM SIGMOD Record
The centroid method for compressing sets of similar images
Pattern Recognition Letters
Improving the Efficiency of the PPM Algorithm
Problems of Information Transmission
LOCO-I: a low complexity, context-based, lossless image compression algorithm
DCC '96 Proceedings of the Conference on Data Compression
Set redundancy, the enhanced compression model, and methods for compressing sets of similar images
Set redundancy, the enhanced compression model, and methods for compressing sets of similar images
The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS
IEEE Transactions on Image Processing
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Medical imaging applications produce large sets of similar images. Thus a compression technique is necessary to reduce space storage. Lossless compression methods are necessary in such critical applications. Set redundancy compression (SRC) methods exploit the interimage redundancy and achieve better results than individual image compression techniques when applied to sets of similar images. In this paper, we make a comparative study of SRC methods on sample datasets using various archivers. We also propose a new SRC method and compare it to existing SRC techniques.