Fractal image compression of Satellite imageries using variable size of range block

2013 IEEE International Conference on Signal and Image Processing Applications Pub Date : 2013-10-01 DOI:10.1109/ICSIPA.2013.6707998

S. Veenadevi, A. Ananth

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引用次数: 4

Abstract

Fractal image compressions of Standard Lena and Satellite imageries have been carried out for the variable size range block method. The image is partitioned by considering maximum and minimum size of the range block and matching it with the domain block. The domain block size of window K*K are sliding over the entire image in steps of K/2. Affine transformation and entropy coding are applied to achieve fractal compression. The Matlab simulation for the standard Lena, and Satellite imageries have been carried out for three different cases of variable range block sizes. The image is reconstructed using iterative functions and inverse transforms. The results of the fractal compression scheme indicate that for the case Rmax = 16 and Rmin = 8, it is possible to achieve higher Compression Ratio (CR) ~ 16 and good Peak Signal to Noise Ratios (PSNR) ~21 dB for satellite imageries. The fractal compression scheme with variable range methods are found to be better than the fixed range methods for achieving higher compression ratios and PSNR values for satellite imageries. The results are presented and discussed in the paper.

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利用变大小距离块对卫星图像进行分形压缩

对标准Lena图像和卫星图像进行了分形压缩。通过考虑范围块的最大和最小大小，并将其与域块进行匹配，对图像进行分割。窗口K*K的域块大小以K/2的步长在整个图像上滑动。采用仿射变换和熵编码实现分形压缩。对标准Lena图像和卫星图像进行了三种不同的变范围块大小情况下的Matlab仿真。利用迭代函数和逆变换对图像进行重构。分形压缩方案的结果表明，当Rmax = 16, Rmin = 8时，可以获得较高的压缩比(CR) ~ 16和良好的峰值信噪比(PSNR) ~21 dB。变距离分形压缩方案比固定距离分形压缩方案更能提高卫星图像的压缩比和PSNR值。本文对实验结果进行了介绍和讨论。

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2013 IEEE International Conference on Signal and Image Processing Applications

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