An effective fractal image compression algorithm based on plane fitting  被引量:2

An effective fractal image compression algorithm based on plane fitting

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作  者:王兴元 国兴 张丹丹 

机构地区:[1]Faculty of Electronic Information&Electrical Engineering,Dalian University of Technology

出  处:《Chinese Physics B》2012年第9期149-155,共7页中国物理B(英文版)

基  金:Project supported by the National Natural Science Foundation of China (Grant Nos. 61173183, 60973152, and 60573172);the Special Scientific Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20070141014);the Natural Science Foundation of Liaoning Province, China (Grant No. 20082165)

摘  要:A new method using plane fitting to decide whether a domain block is similar enough to a given range block is proposed in this paper. First, three coefficients are computed for describing each range and domain block. Then, the best-matched one for every range block is obtained by analysing the relation between their coefficients. Experimental results show that the proposed method can shorten encoding time markedly, while the retrieved image quality is still acceptable. In the decoding step, a kind of simple line fitting on block boundaries is used to reduce blocking effects. At the same time, the proposed method can also achieve a high compression ratio.A new method using plane fitting to decide whether a domain block is similar enough to a given range block is proposed in this paper. First, three coefficients are computed for describing each range and domain block. Then, the best-matched one for every range block is obtained by analysing the relation between their coefficients. Experimental results show that the proposed method can shorten encoding time markedly, while the retrieved image quality is still acceptable. In the decoding step, a kind of simple line fitting on block boundaries is used to reduce blocking effects. At the same time, the proposed method can also achieve a high compression ratio.

关 键 词:fractal image compression plane fitting peak signal to noise ratio gray image 

分 类 号:TP391.41[自动化与计算机技术—计算机应用技术] O241.5[自动化与计算机技术—计算机科学与技术]

 

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