Context-based Adaptive Lossless Image Codec (CALIC) is one of the most efficient lossless encoding techniques for continuous-tone images. However, its performance is considerably downgraded on images with fewer and widely separated grey levels. As a result of this, CALIC may provide lower compression rates in binary images. In this paper we provide an improved version of CALIC that gives better...

We report on numerical results from a revised hydrodynamic simulation of binary neutron-star orbits near merger. We find that the correction recently identified by Flanagan significantly reduces but does not eliminate the neutron-star compression effect. Although results of the revised simulations show that the compression is reduced for a given total orbital angular momentum, the inner most st...

The main objectives of an engineering document management (EDM) system are outlined. Existing image compression algorithms (eg. ITU Group 4 and JBIG) offer efficient solutions to the storage problem but do not sufficiently support other objectives such as spatial access and fast decoding. We propose a novel method based on JBIG, in which the other objectives are also met. The compression perfor...

LZW Algorithm is the most popular dictionary-based adaptive text compression scheme [l]. In LZW algorithm, a changing dictionary contains common strings that have been encountered so far in the text. Motivation of this research is to explore an on-line variablelength binary encoding. We apply this encoding to LZW codes for remedy of the problem that we discussed in our earlier paper in DCC’95 [...

Traditionally, Markov models have not been successfully used for compression of signal data other than binary image data. Due to the fact that exact substring matches in non-binary signal data are rare, using full resolution conditioning information generally tends to make Markov models learn slowly, yielding poor compression. However, as is shown in this paper, such models can be successfully ...

A new universal noise-robust lossless compression algorithm based on a decremental redundancy approach with Fountain codes is proposed. The binary entropy code is harnessed to compress complex sources with the addition of a preprocessing system in this paper. Both the whole binary entropy range compression performance and the noise-robustness of an existing incremental redundancy Fountain code ...