Our thesis is that high compression efficiency for text and images can be obtained by using sophisticated statistical compression techniques, and that greatly increased speed can be achieved at only a small cost in compression efficiency. Our emphasis is on elegant design and mathematical as well as empirical analysis. We analyze arithmetic coding as it is commonly implemented and show rigorously that almost no compression is lost in the implementation. We show that high-efficiency lossless compression of both text and grayscale images can be obtained by using appropriate models in conjunction with arithmetic coding. We introduce a four-component paradigm for lossless image compression and present two methods that give state of the art compression efficiency. In the text compression area, we give a small improvement on the preferred method in the literature. We show that we can often obtain significantly improved throughput at the cost of slightly reduced compression. The extra speed c...

We present a new method for lossless image compression that gives compression comparable to JPEG lossless mode with about five times the speed. Our method, called FELICS, is based on a novel use of two neighboring pixels for both prediction and error modeling. For coding we use single bits, adjusted binary codes, and Golomb or Rice codes. For the latter we present and analyze a provably good method for estimating the single coding parameter.

Despite the fact that computer memory costs havedecreased dramatically over the past few years, data storage still remains, and will probably always remain, an important cost factor for many large scale database applications. Compressing data in a database system is attractive for two reasons: data storage reduction and performance improvement. Storage reduction is a direct and obvious benefit, while performance improves because smaller amounts of physical data need to be moved for any particular operation on the database. We address several aspects of reversible data compression and compression techniques: 2 general concepts of data compression; 2 a number of compression techniques; 2 a comparison of the effects of compression on common data types; 2 advantages and disadvantages of compressing data; and 2 future research needs.