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ISRN Signal ProcessingVolume 2013 2013, Article ID 539759, 5 pages

Research Article

Department of E.C.E., J.N.T. University, Hyderabad, Andhra Pradesh 500085, India

Department of E.C.E, Priyadarshini College of Engineering and Technology, Nellore, Andhra Pradesh 524004, India

Received 25 June 2013; Accepted 17 July 2013

Academic Editors: I. Guler and S. Kalitzin

Copyright © 2013 Shaik. Mahaboob Basha and B. C. Jinaga. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The research trends that are available in the area of image compression for various imaging applications are not adequate for some of the applications. These applications require good visual quality in processing. In general the tradeoff between compression efficiency and picture quality is the most important parameter to validate the work. The existing algorithms for still image compression were developed by considering the compression efficiency parameter by giving least importance to the visual quality in processing. Hence, we proposed a novel lossless image compression algorithm based on Golomb-Rice coding which was efficiently suited for various types of digital images. Thus, in this work, we specifically address the following problem that is to maintain the compression ratio for better visual quality in the reconstruction and considerable gain in the values of peak signal-to-noise ratios PSNR. We considered medical images, satellite extracted images, and natural images for the inspection and proposed a novel technique to increase the visual quality of the reconstructed image.

Author: Shaik. Mahaboob Basha and B. C. Jinaga

Source: https://www.hindawi.com/


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