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A New Way of Image Compression with Classical Integration and Soft Based Computing
Current Issue
Volume 1, 2013
Issue 1 (December)
Pages: 1-5   |   Vol. 1, No. 1, December 2013   |   Follow on         
Paper in PDF Downloads: 26   Since Aug. 28, 2015 Views: 2582   Since Aug. 28, 2015
Authors
[1]
Sreekumar Narayanan, Fellow, Faculty of Computing, Botho University, Botswana.
Abstract
Image compression is one of the major technologies that enable the revolution of multimedia. Image compression techniques find several applications in the areas like, Internet, digital photography, medical, wireless and document imaging, image archives and databases, security and investigation, printing, scanning, and facsimile. Machine learning algorithms have been used often in image compression. The compression ratio of the image recovered using this algorithm was generally around 8:1 with an image quality much lower than JPEG, one of the most well-known image compression standards. In this paper an image compression algorithm based on wavelet technology is proposed that uses the modified extreme learning machine learning algorithm to achieve better visual quality and on par with JPEG. The result of compression is quite satisfactory and aspiring.
Keywords
Image Compression, Extreme Learning Machine, Wavelet, Soft Computing
Reference
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