Performance Assessment of Fractal Coding on Remote Sensing Images with Different Imaging Modalities
D. Sophin Seeli1, M.K. Jeyakumar2
1D.Sophin Seeli, Research Scholar, Department of Computer Applications, Noorul Islam University, Kumaracoil, (Tamil Nadu), India.
2Dr. M.K. Jeyakumar, Professor, Department of Computer Applications, Noorul Islam University, Kumarakoil, (Tamil Nadu), India.
Manuscript received on July 23, 2013. | Revised Manuscript received on August 13, 2013. | Manuscript published on August 30, 2013. | PP: 230-235 | Volume-2, Issue-6, August 2013. | Retrieval Number: F2044082613/2013©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Image compression coders can be lossy or lossless. Fractal image compression is a lossy image compression technique to achieve high level of compression while preserving the quality of the decompressed image close to that of the original image. The method relies on the fact that in certain images, parts of the image resemble other parts of the same image. The compression 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. It is a new technique in image compression field based on Affine contractive transforms. In the present work the fractal coding techniques are applied for the compression of remotely sensed imageries. Also the results are compared with various imaging modalities and the parameters that affect fractal image compression are studied. The comparison results that fractal image compression techniques are found more effective for compressing remote sensing images.
Keywords: Fractal, Encoding, Self-similarity, Affine transformation, Quad tree partitioning.