New image compression method using logarithmic quantization

M. Rahali, H. Loukil, M. Bouhlel
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Abstract

The compression methods of images based on neural network and wavelet transform gives a limitation in the compression ratio and the reconstructed image quality. To improve the compression ratio without quality degradation of the reconstructed image, we add a phase of pretreatment before the discrete wavelet transform uses the principle of Weber-Fechner law which says that the sensation of the human eye to light is logarithmic. We quantify the image by using the Weber-Fechner law to reduce the entropy of the image before the compression.
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采用对数量化的图像压缩新方法
基于神经网络和小波变换的图像压缩方法在压缩比和重构图像质量方面存在局限性。为了在不降低重建图像质量的前提下提高压缩比,我们在离散小波变换前增加了一段预处理,该预处理利用了人眼对光的感觉是对数的Weber-Fechner定律原理。我们利用韦伯-费希纳定律对图像进行量化,以减少压缩前图像的熵。
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