Open AccessOptimization Before Biomedical Image Compression Using CLAHE and DCS
Author(s) -
Satyawati S. Magar,
Bhavani Sridharan
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i3.27.17884
Subject(s) - adaptive histogram equalization , image compression , compression ratio , computer science , artificial intelligence , computer vision , decorrelation , peak signal to noise ratio , histogram equalization , data compression ratio , compression (physics) , data compression , texture compression , image processing , image (mathematics) , materials science , engineering , composite material , internal combustion engine , automotive engineering
In current years, improving the Compression Ratio (CR) in medical imaging is essential and becomes big challenge in the field of biomedical. In that direction we have done optimization before biomedical image compression. For the same we have used the image enhancement techniques. For the enhancement of an image we have used Contrast Limited Adaptive Histogram Equalization (CLAHE) and Decorrelation Stretch (DCS) algorithms. By optimizing an image before compression we have achieved better Compression Ratio (CR) and Peak Signal to Noise Ratio (PSNR) than existing methods of an image compression. Mainly results are compared with Oscillation Concept method of an image compression with and without optimization.