Introduction to parallel algorithms and architectures: array, trees, hypercubes
Introduction to parallel algorithms and architectures: array, trees, hypercubes
ICS '90 Proceedings of the 4th international conference on Supercomputing
The Parallel Evaluation of General Arithmetic Expressions
Journal of the ACM (JACM)
Forward-adaptive method for context-based compression of large binary images
Software—Practice & Experience
Practical Pram Programming
Realization of PRAMs: Processor Design
WDAG '94 Proceedings of the 8th International Workshop on Distributed Algorithms
Parallel Design of Q-Coders for Bilevel Image Compression
Proceedings of the 1994 International Conference on Parallel and Distributed Systems
Parallelism in random access machines
STOC '78 Proceedings of the tenth annual ACM symposium on Theory of computing
An overview of the basic principles of the Q-Coder adaptive binary arithmetic coder
IBM Journal of Research and Development - Q-Coder adaptive binary arithmetic coder
Probability estimation for the Q-Coder
IBM Journal of Research and Development - Q-Coder adaptive binary arithmetic coder
IEEE Transactions on Circuits and Systems for Video Technology
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Binary images can be compressed efficiently using context-based statistical modeling and arithmetic coding. However, this approach is fully sequential and therefore additional computing power from parallel computers cannot be utilized. We attack this problem and show how to implement the context-based compression in parallel. Our approach is to segment the image into non-overlapping blocks, which are compressed independently by the processors. We give two alternative solutions about how to construct, distribute and utilize the model in parallel, and study the effect on the compression performance and execution time. We show by experiments that the proposed approach achieves speedup that is proportional to the number of processors. The work efficiency exceeds 50 % with any reasonable number of processors.