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Article Details

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.

A Proposed Approach for Image Compression based on Wavelet Transform and Neural Network

Author 1: Houda Chakib
Author 2: Brahim Minaoui
Author 3: Mohamed Fakir
Author 4: Abderrahim Salhi
Author 5: Imad Badi

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2017.080959

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 9, 2017.

  • Abstract and Keywords
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Abstract: Over the last years, wavelet theory has been used with great success in a wide range of applications as signal de-noising and image compression. An ideal image compression system must yield high-quality compressed image with high compression ratio. This paper attempts to find the most useful wavelet function to compress an image among the existing members of wavelet families. Our idea is that a backpropagation neural network is trained to select the suitable wavelet function between the two families: orthogonal (Haar) and biorthogonal (bior4.4), to be used to compress an image efficiently and accurately with an ideal and optimum compression ratio. The simulation results indicated that the proposed technique can achieve good compressed images in terms of peak signal to noise ratio (PSNR) and compression ratio (t) in comparison with random selection of the mother wavelet.

Keywords: Haar wavelet transform; biorthogonal wavelet; backpropagation neural network; scaled conjugate gradient algorithm

Houda Chakib, Brahim Minaoui, Mohamed Fakir, Abderrahim Salhi and Imad Badi, “A Proposed Approach for Image Compression based on Wavelet Transform and Neural Network” International Journal of Advanced Computer Science and Applications(IJACSA), 8(9), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080959

@article{Chakib2017,
title = {A Proposed Approach for Image Compression based on Wavelet Transform and Neural Network},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080959},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080959},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {9},
author = {Houda Chakib and Brahim Minaoui and Mohamed Fakir and Abderrahim Salhi and Imad Badi}
}


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