Parallel Lossless Image Compression Using Huffman and Arithmetic Coding

We show that high-resolution images can be encoded and decoded e ciently in parallel. We present an algorithm based on the hierarchical MLP method, used either with Hu man coding or with a new variant of arithmetic coding called quasi-arithmetic coding. The coding step can be parallelized, even though the codes for di erent pixels are of di erent lengths; parallelization of the prediction and error modeling components is straightforward

Gbit/second lossless data compression hardware

This thesis investigates how to improve the performance of lossless data compression hardware as a tool to reduce the cost per bit stored in a computer system or transmitted over a communication network. Lossless data compression allows the exact reconstruction of the original data after decompression. Its deployment in some high-bandwidth applications has been hampered due to performance limitations in the compressing hardware that needs to match the performance of the original system to avoid becoming a bottleneck. Advancing the area of lossless data compression hardware, hence, offers a valid motivation with the potential of doubling the performance of the system that incorporates it with minimum investment. This work starts by presenting an analysis of current compression methods with the objective of identifying the factors that limit performance and also the factors that increase it. [Continues.

The implementation of a lossless data compression module in an advanced orbiting system: Analysis and development

Data compression has been proposed for several flight missions as a means of either reducing on board mass data storage, increasing science data return through a bandwidth constrained channel, reducing TDRSS access time, or easing ground archival mass storage requirement. Several issues arise with the implementation of this technology. These include the requirement of a clean channel, onboard smoothing buffer, onboard processing hardware and on the algorithm itself, the adaptability to scene changes and maybe even versatility to the various mission types. This paper gives an overview of an ongoing effort being performed at Goddard Space Flight Center for implementing a lossless data compression scheme for space flight. We will provide analysis results on several data systems issues, the performance of the selected lossless compression scheme, the status of the hardware processor and current development plan

Parallel data compression

Data compression schemes remove data redundancy in communicated and stored data and increase the effective capacities of communication and storage devices. Parallel algorithms and implementations for textual data compression are surveyed. Related concepts from parallel computation and information theory are briefly discussed. Static and dynamic methods for codeword construction and transmission on various models of parallel computation are described. Included are parallel methods which boost system speed by coding data concurrently, and approaches which employ multiple compression techniques to improve compression ratios. Theoretical and empirical comparisons are reported and areas for future research are suggested