Achieving Better Compression Applying Index-based Byte-Pair Transformation before Arithmetic Coding

Doshi, Jyotika; Gandhi, Savita

doi:10.5120/15783-4555

Cited by 1 publication

(2 citation statements)

References 23 publications

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“…In most of the source data, adjacent bytes are observed to be repeated many times [7]. Therefore, it is a better source for achieving data compression where 2-bytes are replaced with single byte.…”

Section: Literature Reviewmentioning

confidence: 99%

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Byte Pair Transformation using Zero-Frequency Bytes with Varying Number of Passes

Doshi¹,

Gandhi²

2014

IJCA

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Byte pair encoding (BPE) algorithm was suggested by P. Gage is to achieve data compression. It encodes all instances of most frequent byte-pair using zero-frequency byte in the source data. This process is repeated for maximum m possible number of passes until no further compression is possible, either because there are no more frequently occurring byte pairs or there are no more unused zero-frequency bytes to represent pairs. It writes out substitution information before the encoded data in each pass. This algorithm is very time consuming as it requires to determine most frequent byte-pair in each pass before starting substitution. We have proposed kpass byte-pair transformation algorithm where k may be very very small as compared to maximum possible passes m. Our aim is to minimize the compression time and achieve equvivalent compression rate. Proposed algorithm transforms half of the possible most-frequent byte pairs in each pass except the last. In the last pass, it transforms all remaining possible byte-pairs. This reduced number of passes save the time taken in computing frequency of byte-pairs in maximum m passes. Experimental results have shown that proposed algorithm had taken 3. 213, 9.794, 13.324, 16.323, 22.388 seconds with 1, 2, 3, 4 and 6 passes respectively as compared to 295.642 seconds of m-passes. Compression rate achieved due to transformation is 14.72%, 20.12%, 21.89%, 22.67% and 22.96% with 1, 2, 3, 4 and 6 passes respectively as compared to 25.55% using maximum m-passes. As the number of passes increases, compression is better with increased execution time. Our aim of achieving speed is achieved with little loss in compression rate.

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Section: Literature Reviewmentioning

confidence: 99%

“…Authors of this paper had proposed QBT-I [6] and BPT-I [7] dictionary based transformation techniques. They are intended to introduce redundancy in the data for second stage conventional data compression techniques.…”

Section: Literature Reviewmentioning

confidence: 99%

Byte Pair Transformation using Zero-Frequency Bytes with Varying Number of Passes

Doshi¹,

Gandhi²

2014

IJCA

Self Cite

View full text Add to dashboard Cite

show abstract

Achieving Better Compression Applying Index-based Byte-Pair Transformation before Arithmetic Coding

Abstract: Arithmetic coding is used in many compression techniques during the entropy encoding stage. Further compression is not possible without changing the data model and increasing redundancy in the data set. To increase the redundancy, we have applied index based byte-pair transformation (BPT

Cited by 1 publication

References 23 publications

Byte Pair Transformation using Zero-Frequency Bytes with Varying Number of Passes

Byte Pair Transformation using Zero-Frequency Bytes with Varying Number of Passes

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