Near-lossless image compression by combining wavelets and CALIC

Xiaolin Wu, P. Bao
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引用次数: 9

Abstract

In this paper we report experimental work on L/sub /spl infin//-constrained high-fidelity image compression. In our experiments minimum-entropy pre-quantization and minimum-entropy trellis quantization did not lead to competitive L/sub /spl infin//-constrained near-lossless compression performance against our previous work of L/sub /spl infin//-constrained CALIC (Wu et al. 1997). But we were able to improve L/sub /spl infin//-constrained CALIC, the best L/sub /spl infin//-constrained image coder for error tolerance below 7 so far by a hybrid approach. First, an input image is wavelet transformed, the wavelet coefficients are quantized in an L/sub /spl infin// criterion and entropy coded. Then a wavelet approximation of the image is constructed by inverse transform based on the quantized wavelet coefficients. Finally, L/sub /spl infin//-constrained CALIC is used to compress the residue image between the wavelet approximation and the original.
结合小波和CALIC的近无损图像压缩
在本文中,我们报告了L/sub /spl infin//约束的高保真图像压缩的实验工作。在我们的实验中,最小熵预量化和最小熵网格量化并没有导致与我们之前的L/sub /spl infin//约束CALIC相比具有竞争力的L/sub /spl infin//约束的近无损压缩性能(Wu et al. 1997)。但是我们能够通过混合方法改进L/sub /spl infin//-constrained CALIC,这是迄今为止容错度低于7的最佳L/sub /spl infin//-constrained图像编码器。首先对输入图像进行小波变换,将小波系数按L/sub /spl infin//准则量化,并进行熵编码。然后基于量化后的小波系数进行逆变换,构造图像的小波近似。最后,利用L/sub /spl infin//-约束CALIC对小波逼近与原始图像之间的残差图像进行压缩。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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