Fractal Image Compression Based on High Entropy Values Technique


  • Douaa Younis Abbaas Departement of Computer Science, College of Science, Mustansiriyah University, IRAQ.



Fractal Image Compression, Entropy, Image Quality, Domain Pool, Similarity, En-coding


There are many attempts tried to improve the encoding stage of FIC because it consumed time. These attempts worked by reducing size of the search pool for pair range-domain matching but most of them led to get a bad quality, or a lower compression ratio of reconstructed image. This paper aims to present a method to improve performance of the full search algorithm by combining FIC (lossy compression) and another lossless technique (in this case entropy coding is used). The entropy technique will reduce size of the domain pool (i. e., number of domain blocks) based on the entropy value of each range block and domain block and then comparing the results of full search algorithm and proposed algorithm based on entropy technique to see each of which give best results (such as reduced the encoding time with acceptable values in both compression quali-ty parameters which are C. R (Compression Ratio) and PSNR (Image Quality). The experimental results of the proposed algorithm proven that using the proposed entropy technique reduces the encoding time while keeping compression rates and reconstruction image quality good as soon as possible.


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Original Article

How to Cite

D. Y. Abbaas, “Fractal Image Compression Based on High Entropy Values Technique”, Al-Mustansiriyah Journal of Science, vol. 28, no. 2, pp. 119–133, Apr. 2018, doi: 10.23851/mjs.v28i2.507.

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