Paper
22 March 1996 Image coding using parallel implementations of the embedded zerotree wavelet algorithm
Author Affiliations +
Proceedings Volume 2668, Digital Video Compression: Algorithms and Technologies 1996; (1996) https://doi.org/10.1117/12.235405
Event: Electronic Imaging: Science and Technology, 1996, San Jose, CA, United States
Abstract
We explore here the implementation of Shapiro's embedded zerotree wavelet (EZW) image coding algorithms on an array of parallel processors. To this end, we first consider the problem of parallelizing the basic wavelet transform, discussing past work in this area and the compatibility of that work with the zerotree coding process. From this discussion, we present a parallel partitioning of the transform which is computationally efficient and which allows the wavelet coefficients to be coded with little or no additional inter-processor communication. The key to achieving low data dependence between the processors is to ensure that each processor contains only entire zerotrees of wavelet coefficients after the decomposition is complete. We next quantify the rate-distortion tradeoffs associated with different levels of parallelization for a few variations of the basic coding algorithm. Studying these results, we conclude that the quality of the coder decreases as the number of parallel processors used to implement it increases. Noting that the performance of the parallel algorithm might be unacceptably poor for large processor arrays, we also develop an alternate algorithm which always achieves the same rate-distortion performance as the original sequential EZW algorithm at the cost of higher complexity and reduced scalability.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Charles D. Creusere "Image coding using parallel implementations of the embedded zerotree wavelet algorithm", Proc. SPIE 2668, Digital Video Compression: Algorithms and Technologies 1996, (22 March 1996); https://doi.org/10.1117/12.235405
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Cited by 24 scholarly publications.
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KEYWORDS
Image processing

Wavelets

Image compression

Computer programming

Parallel computing

Algorithm development

Array processing

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