Hwan Young Yoo, Bong Han Choi

The Transactions of the Korea Information Processing Society (1994 ~ 2000), Vol. 7, No. 2, pp. 365-372, Feb. 2000
10.3745/KIPSTE.2000.7.2.365,   PDF Download:

Abstract

This paper introduces evolutionary computing to Fractal Image Compression(FIC). In Fractal Image Compression(FIC) a partitioning of the image into ranges is required. As a solution to this problem, there is a propose that evolution computation should be applied in image partitionings. Here ranges are connected sets of small square image blocks. Populations consist of configurations, each of which is a partitioning with a fractal code. In the evolution each configuration produces children who inherit their parent partitionings except for two random neighboring ranges which are merged. From the offspring the best ones are selected for the next generation population based on a fitness criterion Collage Theorem. As the optimum image includes duplication in image data, it gets smaller in saving space, more efficient in speed and more capable in image quality than any other technique in which other coding is used. Fractal Image Compression(FIC) using evolution computation in multimedia image processing applies to such fields as recovery of image and animation which needs a high-quality image and a high image-compression ratio.

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