enhancement huffman for compression of mult files

enhancement huffman for compression of mult files -...

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# Abstract This paper introduces a fixed-length which is based on the Hamming (FLH) algorithm to compress multimedia files. The FLH and Huffman (HU) coding were investigated and tested on different multimedia files. The results indicate that the FLH following HU and HU following FLH enhance the compression ratio and the entropy. Keywords Compression Ratio, Data Compression, Entropy, Fixed-Length, Hamming, Huffman Coding. I. INTRODUCTION HE aim of multimedia files compression is to reduce the redundancy in stored and communication data. The data compression-including multimedia files- is often referred to as coding [13]. It has important applications in data transmission and data storage; reduces either storage or/and communication cost or both. The data compression algorithms are classified into lossless and lossy [1], [13]. A lossless means that when you restore (decompress) a compressed file you get the same as the original one. Examples of such files are: executable code, word processing files, and tabulated numbers. A lossy technique allows data files-such that those which represent images and other acquired patterns-do not have to be kept in perfect condition for storage or transmission. In this paper, we tested lossless algorithms. In order to select the best compression method, you need to compare between the methods in metrics such as: Compression Size (CS), Compression Ratio (CR), Processing Time (PT) or compression and decompression speed, and Entropy (E). The CS is defined as the size of the compressed file in bits after compression is done. The CR is the percentage that results from dividing the CS by the original size of the original file. The PT is the execution time of compressing and/or decompressing a file. The E measures the bits/symbol by dividing the CS by the number of symbols in the original file. One factor that affects the CR is the symbol probability, Manuscript submitted November 21, 2004. This work was performed while in leave at the Amman Arab Universities for Graduate Studies, Amman – Jordan, 2003/2004. A. A. Sharieh is with the Department of Computer Science, King Abdullah School for Information Technology, The University of Jordan, Amman, Jordan; fax: (962-6) 53550704 (e-mail: ( sharieh@ju.edu.jo ). which is calculated by dividing the frequency of this symbol- in the original file- by the total number of all symbols in this file. Another factor which affects the performance is the contents of the file. A third one is code words or table attached with the compressed file for future decompressing. The next section reviews the Huffman coding (HC). Section III explains the Fixed-Length coding based on the Hamming code (FLH). Section IV presents the testing results. Section V concludes the paper. II. HUFFMAN CODING
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This note was uploaded on 02/28/2008 for the course CSCI 576 taught by Professor Smita during the Spring '08 term at USC.

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enhancement huffman for compression of mult files -...

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