High Performance Lossless Multimedia Data Compression through Improved Dictionary
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10.5120/1444-1953 |
K R Kolhe, P R Devale and P Shrivastava. Article:High Performance Lossless Multimedia Data Compression through Improved Dictionary. International Journal of Computer Applications 10(1):29–35, November 2010. Published By Foundation of Computer Science. BibTeX
@article{key:article,
author = {K. R. Kolhe and P. R. Devale and P. Shrivastava},
title = {Article:High Performance Lossless Multimedia Data Compression through Improved Dictionary},
journal = {International Journal of Computer Applications},
year = {2010},
volume = {10},
number = {1},
pages = {29--35},
month = {November},
note = {Published By Foundation of Computer Science}
}
Abstract
The advent of modern electronic world has opened up various fronts in multimedia interaction. They are used in various fields for various purposes of education, entertainment, research and many more. This has led to storage and retrieval of multimedia content regularly. But due to limitations of current technology the disk space and the transmission bandwidth fall behind in the race with the requirement of multimedia content. This imposes a need to compress multimedia content so that they can be easily stored requiring lesser space and easily transferred from one point to another. Some online dictionary based compression technique can be applied to reduce the data packet size. When the repetition rate of the same symbols within the data are high the compression techniques works very well. During the process of encoding and decoding, the building of online dictionary in the primary memory ensures the single pass over the data, and the dictionary need not to be transmitted over the network. Our proposed Improved Dictionary technique scans the data byte-wise, so that the chances of repetition of individual symbols are higher for text messages. Fixed length coding transmits fixed length codes for all dictionary entries. For bigger messages better optimization in terms of size reduction can be achieved through variable length coding with L-Z technique, where transmitted code length corresponding to individual dictionary entries will vary according to the requirement dynamically.
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