Self-synchronizing Huffman codes (Corresp.)

Ferguson, T.; Rabinowitz, Joshua H.

doi:10.1109/tit.1984.1056931

Cited by 154 publications

(62 citation statements)

References 6 publications

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“…This leads to a loss of around 3 percentage points in compression ratio, but makes TH a fast self-synchronizing code, 8 which can be directly 8 That is, it is possible to detect quickly the beginning of searched for a compressed pattern with any string matching algorithm. While most Huffman codes have the property of self-synchronization [17], this may require processing an arbitrary number of codewords. Some compressors introduce synchronization strings or marks to force the resynchronization after a given number of bits/bytes [18,19].…”

Section: Word-based Text Compressionmentioning

confidence: 99%

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Boosting Text Compression with Word-Based Statistical Encoding

Fariña

Navarro

Paramá

2011

The Computer Journal

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Semistatic word-based byte-oriented compressors are known to be attractive alternatives to compress natural language texts. With compression ratios around 30-35%, they allow fast direct searching of compressed text. In this article we reveal that these compressors have even more benefits. We show that most of the state-of-the-art compressors benefit from compressing not the original text, but the compressed representation obtained by a word-based byte-oriented statistical compressor. For example, p7zip with a dense-coding preprocessing achieves even better compression ratios and much faster compression than p7zip alone. We reach compression ratios below 17% in typical large English texts, which was obtained only by the slow PPM compressors. Furthermore, searches perform much faster if the final compressor operates over word-based compressed text. We show that typical self-indexes also profit from our preprocessing step. They achieve much better space and time performance when indexing is preceded by a compression step. Apart from using the well-known Tagged Huffman code, we present a new suffix-free Dense-Code-based compressor that compresses slightly better. We also show how some self-indexes can handle non-suffix-free codes. As a result, the compressed/indexed text requires around 35% of the space of the original text and allows indexed searches for both words and phrases. * A preliminary partial version of this work appeared in [1].

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Section: Word-based Text Compressionmentioning

confidence: 99%

“…17 • The Re-pair 18 compressor coupled with a bitoriented Huffman. 19 • Gnu gzip, 20 a Ziv-Lempel-based compressor.…”

Section: Boosting Compressionmentioning

confidence: 99%

Boosting Text Compression with Word-Based Statistical Encoding

Fariña

Navarro

Paramá

2011

The Computer Journal

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“…For certain distributions, a Huffman code may be constructed that includes synchronizing codewords or sequences [19,20]. These are codewords or sequences after the occurrence of which decoding will be correct, regardless of any possible error before them.…”

Section: Synchronizationmentioning

confidence: 99%

Parallel Huffman Decoding with Applications to JPEG Files

Klein¹

2003

The Computer Journal

109

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A simple parallel algorithm for decoding a Huffman encoded file is presented, exploiting the tendency of Huffman codes to resynchronize quickly, i.e. recovering after possible decoding errors, in most cases. The average number of bits that have to be processed until synchronization is analyzed and shows good agreement with empirical data. As Huffman coding is also a part of the JPEG image compression standard, the suggested algorithm is then adapted to the parallel decoding of JPEG files.

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“…This is a data source that is known to have highly variable data lengths from block to block. Values for pk(x) and qk(x) have been found by iterative use of (4) and (5). From this, a prediction of the number of bits still to be placed at stage 5 has been found.…”

Section: A Bit Placementmentioning

confidence: 99%

“…This is idue to errors that cause the decoder to lose synchronization with the start and end of blocks. Even in codes where synchronization is regained after the loss of a few blocks [4], [5], the block count is likely to be permanently offset, resulting in the following data being decoded at the wrong location. For some applications, e.g., speech, this may not be a problem as it may only cause a temporal shift in the following data.…”

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confidence: 99%

The EREC: an error-resilient technique for coding variable-length blocks of data

Redmill

Kingsbury

1996

IEEE Trans. on Image Process.

220

103

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Abstract-Many source :and data compression schemes work by splitting the input signall into blocks and producing variablelength coded data for each block. If these variable-length blocks are transmitted consecutively, then the resulting coder is highly sensitive to channel errors. Synchronization code words are often used to provide occasional iresynchronization at the expense of a some added redundant information. This paper introduces the error-resilient entropy code (EREC) as a method for adapting existing schemes to give increased resilience to random and lburst errors while maintaining high compression. The EREC has been designed to exhibit graceful degradation with worsening channel conditions. The EREC is applicable to many problems and is particularly effective when the more important information is transmitted near the start of each variable-length block and is not dependent on following data.The EREC has been apiplied to both still image and video compression schemes, using, the discrete cosine transform (DCT) and variable-length coding. The results have been compared to schemes using synchronization code words, and a large improvement in performance for noisy channels has been observed.

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Self-synchronizing Huffman codes (Corresp.)

Cited by 154 publications

References 6 publications

Boosting Text Compression with Word-Based Statistical Encoding

Boosting Text Compression with Word-Based Statistical Encoding

Parallel Huffman Decoding with Applications to JPEG Files

The EREC: an error-resilient technique for coding variable-length blocks of data

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