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Wavelet Filter Adjusting for Image Lossless Compression Using Pattern Recognition

机译:利用模式识别的小波滤波器调整,实现图像无损压缩

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A method for image lossless compression using lifting scheme wavelet transform is presented. The proposed method adjusts wavelet filter coefficients analyzing signal spectral characteristics to obtain a higher compression ratio in comparison to the standard CDF(2,2) and CDF(4,4) filters. The proposal is based on spectral pattern recognition with 1-NN classifier. Spectral patterns of a small fixed length are formed for the entire image permitting thus the global optimization of the filter coefficients, equal for all decompositions. The proposed method was applied to a set of test images obtaining better results in entropy values in comparison to the standard wavelet lifting filters.
机译:提出了一种基于提升方案小波变换的图像无损压缩方法。与标准CDF(2,2)和CDF(4,4)滤波器相比,该方法可调整分析信号频谱特征的小波滤波器系数,以获得更高的压缩率。该提议基于具有1-NN分类器的光谱模式识别。对于整个图像形成固定长度小的光谱图案,从而允许滤波器系数的全局最优化,对于所有分解都相同。与标准的小波提升滤波器相比,该方法被应用于一组测试图像,在熵值上获得了更好的结果。

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