Asymmetric lossless image compression

Abstract

Summary form only given. Lossless image compression is often required in situations where compression is done once and decompression is to be performed a multiple number of times. Since compression is to be performed only once, time taken for compression is not a critical factor while selecting an appropriate compression scheme. What is more critical is the amount of time and memory needed for decompression and also the compression ratio obtained. Compression schemes that satisfy the above constraints are called asymmetric techniques. While there exist many asymmetric techniques for the lossy compression of image data, most techniques reported for lossless compression of image data have been symmetric. We present a new lossless compression technique that is well suited for asymmetric applications. It gives superior performance compared to standard lossless compression techniques by exploiting 'global' correlations. By 'global' correlations we mean similar patterns of pixels that re-occur within the image, not necessarily at close proximity. The developed technique can also potentially be adapted for use in symmetric applications that require high compression ratios. We develop algorithms for codebook design using LBG like clustering of image blocks. For the sake of a preliminary investigation, codebooks of various sizes were constructed using different block sizes and using the 8 JPEG predictors as the set of prediction schemes.