Open AccessThe Noise Reduction over Wireless Channel Using Vector Quantization Compression and Filtering
Author(s) -
Iman Elawady,
Abdelmounaïm Moulay Lakhdar,
Mustapha Khelifi
Publication year - 2016
Publication title -
international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.277
H-Index - 22
ISSN - 2088-8708
DOI - 10.11591/ijece.v6i1.pp130-138
Subject(s) - codebook , vector quantization , computer science , linde–buzo–gray algorithm , quantization (signal processing) , wireless , channel (broadcasting) , robustness (evolution) , algorithm , data compression , image compression , noise reduction , artificial intelligence , transmission (telecommunications) , data transmission , telecommunications , image processing , computer network , image (mathematics) , biochemistry , chemistry , gene
The transmission of compressed data over wireless channel conditions represents a big challenge. The idea of providing robust transmission gets a lot of attention in field of research. In this paper we study the effect of the noise over wireless channel. We use the model of Gilbert-Elliot to represent the channel. The parameters of the model are selected to represent three cases of channel. As data for transmission we use images in gray level size 512x512. To minimize bandwidth usage we compressed the image with vector quantization also in this compression technique we study the effect of the codebook in the robustness of transmission so we use different algorithms to generate the codebook for the vector quantization finally we study the restoration efficiency of received image using filtering and indices recovery technique.