Context-based Lossless Image Compression

Abstract

The two-dimensional method of Langdon and Rissanen for compression of black and white images is extended to handle the exact lossless compression of grey-scale images. Neighbouring pixel values are used to define contexts and probabilities associated with the contexts are used to compress the image. The problem of restricting the number of contexts, both to limit the storage requirements and to be able to obtain sufficient data to generate meaningful probabilities, is addressed. Investigations on a variety of images are carried using the JPEG lossless mode predictors. Results indicate that a one pass arithmetic encoder using restricted contexts can lead to effective lossless image compression algorithms.