DocumentCode
3281969
Title
Multiple Subgroup Data Compression Technique Based on Huffman Coding
Author
Shukla, Piyush Kumar ; Rusiya, Pradeep ; Agrawal, Deepak ; Chhablani, Lata ; Raghuwanshi, Balwant Singh
Author_Institution
CSE, UIT, Bhopal, India
fYear
2009
fDate
23-25 July 2009
Firstpage
397
Lastpage
402
Abstract
There are so many records compression methods have been introduced to shrink the phrasing/data cargo space and communication costs. The intelligent compression method in this article is based on switching code information compression technique with the utility of adaptive Huffman coding. The programming development of the structure encodes usually occurring characters with shorter bit code and infrequently occurring appearing characters with longer bit codes, same code can be use for three symbols for numbers, alphabet, and special character. The decoding process regenerate the encoded data by expanding the encoded data back to the original data and works very much like the encoder process. Proposed method is more effective than adaptive Huffman coding because it reduce the codeword length of the characters and can be use same codeword for three different groups character. Their size of the symbol-codeword table is also reduces which transmitted with the compressed data. This process enhancing compression efficiency up to 12% more than adaptive Huffman coding which provide compression ratio up to 52.51% (+12%). The propose system is very impressive for compressing text file, which hold numbers and special symbols approximately equi-probable to alphabets like Mathpsilas Books/database files in a real time environment.
Keywords
Huffman codes; adaptive codes; data compression; decoding; adaptive Huffman coding; codeword length; compression efficiency; decoding process; intelligent compression method; multiple subgroup data compression technique; real time environment; switching code information; symbol-codeword table; text file; Application software; Computational intelligence; Costs; Data communication; Data compression; Decoding; Entropy; Huffman coding; Image coding; Memory; Adaptive Huffman Coding; Block to Variable Code; Data Compression System (DCS); Huffman tree; Optimal Prefix Tree; Switching Code;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence, Communication Systems and Networks, 2009. CICSYN '09. First International Conference on
Conference_Location
Indore
Print_ISBN
978-0-7695-3743-6
Type
conf
DOI
10.1109/CICSYN.2009.86
Filename
5231893
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