CONTEXT BASED LOSSLESS COMPRESSION OF IMAGES.

Abstract

There are numerous applications of image processing, such as satellite imaging, medical imaging, and video where the image size or image stream size is too large and requires a large amount of storage space or high bandwidth for communication in its original form. It would be obvious that the present and future applications in multimedia and other areas would focus on the problem of optimizing storage space and transmission bandwidth. Image compression techniques can be used effectively in such applications. Lossless (reversible) image compression techniques preserve the information so that exact reconstruction of the image is possible from the compressed data. In this thesis the author describes the existing lossless compression schemes and also presents a new technique based on the concept of Context modeling which exploits the spatial dependencies between the individual pixels to improve the Compression ratio.