Conference Paper

An effieient algorithm for fractal image coding using kick-out and zero contrast conditions

Dept. of Electron. & Inf. Eng., Hong Kong Polytech. Univ., China
DOI: 10.1109/ISCAS.2003.1206014 Conference: Circuits and Systems, 2003. ISCAS '03. Proceedings of the 2003 International Symposium on, Volume: 2
Source: DBLP


In this paper, we propose a fast algorithm for fractal image coding based on a single kick-out condition and zero contrast prediction. The single kick-out condition can eliminate lots of unmatched domain blocks in the early encoding phase. An efficient method based on zero contrast prediction is also proposed, which can determine whether the contrast factor for a domain block is zero or not and compute the corresponding difference between the range block and the transformed domain block efficiently and exactly. The proposed algorithm can achieve the same reconstructed image quality as the exhaustive search, and can greatly reduce the required computational complexity. In addition, this algorithm does not need any preprocessing steps and additional memory for its implementation, and can combine with other fast fractal algorithms to further improve the speed. Experimental results show that the runtime is reduced by about 50% when compared to the exhaustive search method. The runtime can be reduced by about 75% when our algorithm is combined with the DCT inner product algorithm.

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Available from: Kin-Man Lam, Jul 11, 2014
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    ABSTRACT: An approach based on fast local area search is proposed to reduce the computation time of fractal image coding which increases the power consumption of embedded system. The algorithm starts from a code computed by collage coding and keeps on improving this code with a heuristic until convergence to a locally optimal solution. Experimental result shows that compared with the conventional fractal coding method PIFS, the coding speed and compression ratio is increased significantly and power consumption of embedded system is decreased about 8%~12%, while the signal to noise ratio of it and the decoding image quality is acceptable.
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