Open AccessBASED ON RANGE AND DOMAIN FRACTAL IMAGE COMPRESSION OF SATELLITE IMAGERIES IMPROVED ALGORITHM FOR RESEARCH
Author(s) -
Saema Enjela,
A. Ananth
Publication year - 2014
Publication title -
international journal of electrical and electronics engineering
Language(s) - English
Resource type - Journals
ISSN - 2231-5284
DOI - 10.47893/ijeee.2014.1130
Subject(s) - fractal transform , fractal compression , image compression , block truncation coding , fractal , color cell compression , lossy compression , data compression , algorithm , computer vision , computer science , artificial intelligence , mathematics , compression ratio , image processing , image (mathematics) , mathematical analysis , internal combustion engine , automotive engineering , engineering
Fractal coding is a novel method to compress images, which was proposed by Barnsley, and implemented by Jacquin. It offers many advantages. Fractal image coding has the advantage of higher compression ratio, but is a lossy compression scheme. The encoding procedure consists of dividing the image into range blocks and domain blocks and then it takes a range block and matches it with the domain block. The image is encoded by partitioning the domain block and using affine transformation to achieve fractal compression. The image is reconstructed using iterative functions and inverse transforms. However, the encoding time of traditional fractal compression technique is too long to achieve real-time image compression, so it cannot be widely used. Based on the theory of fractal image compression; this paper raised an improved algorithm form the aspect of image segmentation. In the present work the fractal coding techniques are applied for the compression of satellite imageries. The Peak Signal to Noise Ratio (PSNR) values are determined for images namely Satellite Rural image and Satellite Urban image. The Matlab simulation results for the reconstructed image shows that PSNR values achievable for Satellite Rural image ~33 and for Satellite urban image ~42.