Park Kyung Bae, Jung Woo Suk, Kim Jung Il, Jeong Keun Won, Lee Kwang Bae, Kim Hyen Ug

The Transactions of the Korea Information Processing Society (1994 ~ 2000), Vol. 2, No. 5, pp. 691-700, Sep. 1995
10.3745/KIPSTE.1995.2.5.691,   PDF Download:

Abstract

Most fractal image codings using fractal concept require long encoding time because a large amount of computation is needed to find an optimal affine transformation point. Such a problem can be solved by designing a block classifier fitted to characteristics of image blocks. In general, it is possible to predict more precise and various types of blocks in frequency domain than in spatial domain. In this paper, we propose a block classifier to predict the block type using characteristics of DCT(Discrete Cosine Transform). This classifier has merits to enhance the quality of decoded images as well as to reduce the encoding time by meeting fractal features. AC coefficient values in frequency domain make it possible to predict various types of blocks. As the results, the number of comparisons between a range block and the corresponding domain blocks to reach an optimal affine transformation point can be reduced. Specially, signs of DCT coefficients help to find the optimal affine transformation point with only two isometric transformations by eliminating unnecessary isometric transformations among eight isometric transformations used in traditional fractal codings.

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