2005
DOI: 10.1016/j.dam.2004.04.013
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Parallel Lempel Ziv coding

Abstract: We explore the possibility of using multiple processors to improve the encoding and decoding times of Lempel-Ziv schemes. A new layout of the processors, based on a full binary tree, is suggested and it is shown how LZSS and LZW can be adapted to take advantage of such parallel architectures. The layout is then generalized to higher order trees. Experimental results show an improvement in compression over the standard method of parallelization and an improvement in time over the sequential method.

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Cited by 57 publications
(28 citation statements)
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“…This flexibility will not be available when using standard Operating System memory management and data acquisition mechanisms which are completely separated in an all-purpose Operating System. In the future we consider adapting parallel approaches [23,24] so as to make the suggested infrustructure suitable for parallel processing.…”
Section: Discussionmentioning
confidence: 99%
“…This flexibility will not be available when using standard Operating System memory management and data acquisition mechanisms which are completely separated in an all-purpose Operating System. In the future we consider adapting parallel approaches [23,24] so as to make the suggested infrustructure suitable for parallel processing.…”
Section: Discussionmentioning
confidence: 99%
“…These end-to-end numbers are more relevant than knowledge of actual network bandwidth, because decompression requires the use of receivers' CPU cycles. The sizes of the blocks have been preferred based on the common page size (Weisberg & Wiseman, 2009;Itshak & Wiseman, 2009) and the efficiency of compression techniques derived from Klein & Wiseman (2005). The ratios between the sending time and the reducing speed size have been set according to the statistics detailed in Figure 3.…”
Section: Methods Comparisonmentioning
confidence: 99%
“…Usually, when there is a non-zero value in a latter coefficient, a long sequence of zeros will be before this coefficient. A long sequence of zeros before a non-zero value is a very rare case [22,23], so unlike dictionary codes [24,25] the entropy encoder will yield for this data, a long sequence of bits. This will increase the size of the compressed image.…”
Section: Steganography System Using Jpegmentioning
confidence: 99%