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Automatic filter coefficient calculation in lifting scheme wavelet transform for lossless image compression

机译:升降方案中的自动滤波器系数计算小波变换无损图像压缩

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摘要

In this paper, a new method for automatic filter coefficient calculation in lifting scheme wavelet transform for image lossless compression is proposed. Actually, there is no specific rule for setting filter coefficients (a, b). Therefore, this work proposes an automatic method to calculate the filter coefficients depending on the spectral analysis of each image. Also, filter coefficients are determined for five decomposition levels and for each quadrant through applying the discrete wavelet transform in the lossless image compression problem. Spectral patterns are computed and fixed into small length vectors for building different wavelet decomposition levels; these vectors are automatically computed using a 1-NN classifier. Experimental results over standard images show that calculating the wavelet filter coefficients using the proposed method generates higher compression rates (in entropy and bitstream values) against standard wavelet and linear prediction filters.
机译:在本文中,提出了一种新的自动滤波器系数计算方法,用于图像无损压缩的提升方案小波变换。 实际上,设置滤波器系数(A,B)没有具体规则。 因此,该工作提出了一种自动方法来根据每个图像的光谱分析来计算滤波器系数。 此外,通过在无损图像压缩问题中应用离散小波变换来确定五个分解水平和每个象限的滤波器系数。 将光谱图案计算并固定到小长度向量中以构建不同的小波分解水平; 这些向量使用1-NN分类器自动计算。 通过标准图像的实验结果表明,使用所提出的方法计算小波滤波器系数,可以针对标准小波和线性预测滤波器产生更高的压缩速率(以熵和比特流值)。

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