首页> 外文期刊>International Journal of Wavelets, Multiresolution and Information Processing >ADAPTIVE WAVELETS FOR IMAGE COMPRESSION USING UPDATE LIFTING: QUANTIZATION AND ERROR ANALYSIS
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ADAPTIVE WAVELETS FOR IMAGE COMPRESSION USING UPDATE LIFTING: QUANTIZATION AND ERROR ANALYSIS

机译:使用更新提升的图像压缩自适应小波:量化和误差分析

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Classical linear wavelet representations of images have the drawback that they are not optimally suited to represent edge information. To overcome this problem, nonlinear multiresolution decompositions have been designed to take into account the characteristics of the input signal/image. In our previous work, we have introduced an adaptive lifting framework, that does not require bookkeeping but has the property that it processes edges and homogeneous image regions in a different fashion. The current paper discusses the effects of quantization in such an adaptive wavelet decomposition. We provide conditions for recovering the original decisions at the synthesis and for relating the reconstruction error to the quantization error, Such an analysis is essential for the application of these adaptive decompositions in image compression.
机译:图像的经典线性小波表示具有以下缺点:它们不是最佳地适合于表示边缘信息。为了克服这个问题,已经设计了非线性多分辨率分解来考虑输入信号/图像的特性。在我们以前的工作中,我们引入了一种自适应提升框架,该框架不需要簿记,但具有以不同方式处理边缘和均匀图像区域的特性。目前的论文讨论了在这种自适应小波分解中量化的影响。我们提供了在合成时恢复原始决策以及将重构误差与量化误差相关联的条件。这种分析对于这些自适应分解在图像压缩中的应用至关重要。

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