分类纹理图像的错误隐藏

J. Polec, Michal Pohancenik, S. Ondrusova, K. Kotuliaková, T. Karlubíková
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引用次数: 6

摘要

对于静态图像中的错误掩蔽,了解图像分类是很有必要的。有了一个有效的分类器,我们应该选择一个足够好的方法来恢复缺失的图像片段。这是非常重要的,特别是纹理图像。在这种情况下,常用的方法通常会失败。有必要选择的方法,这是专门用于合成图像或油漆。本文给出了外推和纹理合成的三种方法。分析了它们在恢复缺失纹理图像片段方面的适用性。对于一类纹理分类,进行了多类分类分析。作为缺失的图像片段,我们考虑了8×8的block、16×16的macroblock和strip的macroblock。评估是用客观和主观的标准来完成的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Error concealment for classified texture images
For error masking in the static images, it is good to know image classification. Having an effective classificator, we should achieve selecting a method good enough for restoration of missing image segments. It is very important especially for texture images. Common methods usually fail in these cases. It is necessary to select the method, which is dedicated for synthesizing an image or for inpainting. In this paper, three methods of extrapolation and texture synthesis are shown. They are analysed in terms of suitability for restoration of missing texture image segments. For one type of texture classification, the analysis of several categories is made. As the missing image segments, block of 8×8, macroblock of 16×16 and strip of macroblocks are considered. The evaluation is done using objective as well as subjective criteria.
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