Research Article
Optimized Image Compression through Artificial Neural Networks and Wavelet Theory
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 79 - Issue 13 |
| Published: October 2013 |
| Authors: Raghvendra Pratap Singh, Choudhary Mahfooz Alam, J P Saini |
10.5120/13801-1797
|
Raghvendra Pratap Singh, Choudhary Mahfooz Alam, J P Saini . Optimized Image Compression through Artificial Neural Networks and Wavelet Theory. International Journal of Computer Applications. 79, 13 (October 2013), 21-25. DOI=10.5120/13801-1797
@article{ 10.5120/13801-1797,
author = { Raghvendra Pratap Singh,Choudhary Mahfooz Alam,J P Saini },
title = { Optimized Image Compression through Artificial Neural Networks and Wavelet Theory },
journal = { International Journal of Computer Applications },
year = { 2013 },
volume = { 79 },
number = { 13 },
pages = { 21-25 },
doi = { 10.5120/13801-1797 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2013
%A Raghvendra Pratap Singh
%A Choudhary Mahfooz Alam
%A J P Saini
%T Optimized Image Compression through Artificial Neural Networks and Wavelet Theory%T
%J International Journal of Computer Applications
%V 79
%N 13
%P 21-25
%R 10.5120/13801-1797
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Many techniques have been developed for image compression. An efficient image compression technique promises to give high compression ratio, maintaining the quality of the image. The paper proposes an image compression technique which combines both Artificial Neural Networks and Wavelet theory to optimize the compression ratio and peak signal to noise ratio. Results show that high compression ratio is achievable as per requirement, maintaining good reconstruction quality.
References
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