A New Way of Image Compression with Classical Integration and Soft Based Computing
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Sreekumar Narayanan, Fellow, Faculty of Computing, Botho University, Botswana.
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.
Image Compression, Extreme Learning Machine, Wavelet, Soft Computing
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