多分辨率分段线性图像分解:量化误差传播和“稳定”压缩方案的设计

O. Kiselyov, P. Fisher
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摘要

只提供摘要形式。本文介绍了一种设计稳定的无瓦片效应多分辨率图像压缩方案的新方法。它着重于分解系数中的量化误差如何影响解压缩图像的质量,误差如何在多分辨率分解中传播,以及如何设计最小化量化误差影响的压缩方案(视觉上和定量上)。本文还介绍并分析了最简单的拉普拉斯金字塔族(使用三点因果滤波器),它可以产生多分辨率分段线性图像分解。这使重建图像的视觉效果更好,没有块状物,如例子所示。误差传播分析导致发现了特定的拉普拉斯金字塔,其中量化误差在传播时不会放大,而是迅速衰减。
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Multiresolutional piecewise-linear image decompositions: quantization error propagation and design of "stable" compression schemes
Summary form only given. The paper introduces a new approach to design of stable tile-effect-free multiresolutional image compression schemes. It focuses on how quantization errors in the decomposition coefficients affect the quality of the decompressed picture, how the errors propagate in a multiresolutional decomposition, and how to design a compression scheme where the effect of quantization errors is minimized (visually and quantitatively). It also introduces and analyzes the simplest family of Laplacian pyramids (using 3-point causal filters) which yield multiresolutional piecewise-linear image decompositions. This gives reconstructed images much better visual appearance without blockiness, as the examples. The error propagation analysis has lead to discovery of particular Laplacian pyramids where quantizations errors do not amplify as they propagate, but quickly decay.
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