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.
Highlights
In information theory and coding theory with applications in computer science and telecommunication, error detection and correction or error control are techniques that enable reliable delivery of digital data over unreliable communication channels
Many communication channels are subject to channel noise, and errors may be introduced during transmission from the source to a receiver
The paper is organized as follow: the first part introduce the quaternion wavelets transform (QWT) and vector quantization as bases for compression, in the second part the RS coding with main input paramters, than how to creat the data base of the coding rate acording to inputs conditions, after that introduction to the main bases of Genetic Algorithm (GA), the formulation of solving steps, the simulation results and conclusion
Summary
In information theory and coding theory with applications in computer science and telecommunication, error detection and correction or error control are techniques that enable reliable delivery of digital data over unreliable communication channels. Many communication channels are subject to channel noise, and errors may be introduced during transmission from the source to a receiver. The Reed–Solomon codes are efficient error-correcting codes that used in many important applications. The input parameters can provide good results on the level of receiver this will maximize the number of redundant bits which make us wonder about what is the efficient coding rate that have minimum number of redundant bits. The objective here is to develop the selection of inputs parameters of RS code according to the channel noise using artificial intelligence technique (GA). The paper is organized as follow: the first part introduce the QWT and vector quantization as bases for compression, in the second part the RS coding with main input paramters, than how to creat the data base of the coding rate acording to inputs conditions (limitations), after that introduction to the main bases of GA, the formulation of solving steps, the simulation results and conclusion
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