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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 5, 2016.
Abstract: Many images you see on the Internet today have undergone compression for various reasons. Image compression can benefit users by having pictures load faster and webpages use up less space on a Web host. Image compression does not reduce the physical size of an image but instead compresses the data that makes up the image into a smaller size. In case of image transmission the noise will decrease the quality of recivide image which obliges us to use channel coding techniques to protect our data against the channel noise. The Reed-Solomon code is one of the most popular channel coding techniques used to correct errors in many systems ((Wireless or mobile communications, Satellite communications, Digital television / DVB,High-speed modems such as ADSL, xDSL, etc.). Since there is lot of possibilities to select the input parameters of RS code this will make us concerned about the optimum input that can protect our data with minimum number of redundant bits. In this paper we are going to use the genetic algorithm to optimize in the selction of input parameters of RS code acording to the channel conditions wich reduce the number of bits needed to protect our data with hight quality of received image.
Mustapha Khelifi, Abdelmounaim Moulay Lakhdar and Iman Elawady, “Optimization of Channel Coding for Transmitted Image Using Quincunx Wavelets Transforms Compression” International Journal of Advanced Computer Science and Applications(IJACSA), 7(5), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070556
@article{Khelifi2016,
title = {Optimization of Channel Coding for Transmitted Image Using Quincunx Wavelets Transforms Compression},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070556},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070556},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {5},
author = {Mustapha Khelifi and Abdelmounaim Moulay Lakhdar and Iman Elawady}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.