This paper utilizes a spatial texture correlation and the intelligent classification algorithm （ICA） search strategy to speed up the encoding process and improve the bit rate for fractal image compression. Texture f...This paper utilizes a spatial texture correlation and the intelligent classification algorithm （ICA） search strategy to speed up the encoding process and improve the bit rate for fractal image compression. Texture features is one of the most important properties for the representation of an image. Entropy and maximum entry from co-occurrence matrices are used for representing texture features in an image. For a range block, concerned domain blocks of neighbouring range blocks with similar texture features can be searched. In addition, domain blocks with similar texture features are searched in the ICA search process. Experiments show that in comparison with some typical methods, the proposed algorithm significantly speeds up the encoding process and achieves a higher compression ratio, with a slight diminution in the quality of the reconstructed image; in comparison with a spatial correlation scheme, the proposed scheme spends much less encoding time while the compression ratio and the quality of the reconstructed image are almost the same.展开更多
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. ...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.展开更多
The method of fractal image compression is introduced which is applied to compress the line structured light image. Based on the self similarity of the structured light image, we attain satisfactory compression ratio ...The method of fractal image compression is introduced which is applied to compress the line structured light image. Based on the self similarity of the structured light image, we attain satisfactory compression ratio and higher peak signal to noise ratio (PSNR). The experimental results indicate that this method can achieve high performance.展开更多
A new fractal image compression algorithm based on high frequency energy (HFE) partitioning andmatched domain block searching is presented to code synthetic aperture radar (SAR) imagery. In the hybridcoding algorithm,...A new fractal image compression algorithm based on high frequency energy (HFE) partitioning andmatched domain block searching is presented to code synthetic aperture radar (SAR) imagery. In the hybridcoding algorithm, the original SAR image is decomposed to low frequency components and high frequencycomponents by wavelet transform (WT). Then the coder uses HFE of block to partition and searchthe matched domain block for each range block to code the low frequency components. For the high frequencycomponents, a modified embedded zero-tree wavelet coding algorithm is applied. Experiment resultsshow that the proposed coder obtains about 0. 3dB gain when compared to the traditional fractal coderbased on the quadtree partition. Moreover, the subjective visual quality of the reconstructed SAR imageof the proposed coder outperforms that of the traditional fractal coders in the same compression ratio(CR).展开更多
基金supported by the National Natural Science Foundation of China (Grant Nos. 60573172 and 60973152)the Superior University Doctor Subject Special Scientific Research Foundation of China (Grant No. 20070141014)the Natural Science Foundation of Liaoning Province of China (Grant No. 20082165)
文摘This paper utilizes a spatial texture correlation and the intelligent classification algorithm （ICA） search strategy to speed up the encoding process and improve the bit rate for fractal image compression. Texture features is one of the most important properties for the representation of an image. Entropy and maximum entry from co-occurrence matrices are used for representing texture features in an image. For a range block, concerned domain blocks of neighbouring range blocks with similar texture features can be searched. In addition, domain blocks with similar texture features are searched in the ICA search process. Experiments show that in comparison with some typical methods, the proposed algorithm significantly speeds up the encoding process and achieves a higher compression ratio, with a slight diminution in the quality of the reconstructed image; in comparison with a spatial correlation scheme, the proposed scheme spends much less encoding time while the compression ratio and the quality of the reconstructed image are almost the same.
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)
文摘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.
文摘The method of fractal image compression is introduced which is applied to compress the line structured light image. Based on the self similarity of the structured light image, we attain satisfactory compression ratio and higher peak signal to noise ratio (PSNR). The experimental results indicate that this method can achieve high performance.
基金Supported by the National Natural Science Foundation of China (No. 90304003)the President Fund of GUCAS (No. O85101HM03).
文摘A new fractal image compression algorithm based on high frequency energy (HFE) partitioning andmatched domain block searching is presented to code synthetic aperture radar (SAR) imagery. In the hybridcoding algorithm, the original SAR image is decomposed to low frequency components and high frequencycomponents by wavelet transform (WT). Then the coder uses HFE of block to partition and searchthe matched domain block for each range block to code the low frequency components. For the high frequencycomponents, a modified embedded zero-tree wavelet coding algorithm is applied. Experiment resultsshow that the proposed coder obtains about 0. 3dB gain when compared to the traditional fractal coderbased on the quadtree partition. Moreover, the subjective visual quality of the reconstructed SAR imageof the proposed coder outperforms that of the traditional fractal coders in the same compression ratio(CR).
