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Artifact Reduction in Compressed Images based on Region Homogeneity Constraints using the Projection onto Convex Sets Algorithm

机译:基于凸集算法投影的基于区域同质约束的压缩图像伪影减少

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摘要

In this paper, a novel projection onto convex sets (POCS) method is presented for the suppression of blocking and ringing artifacts in a compressed image that contains homogeneous regions. A new family of convex smoothness constraint sets is introduced, using the uniformity property of image regions. This set of constraints allows different degrees of smoothing in different regions of the image, while preserving the image edges. The regions are segmented using the fuzzy c-means algorithm, which allows ambiguous pixels to be left unclassified. Experimental results on JPEG compressed images demonstrate that the proposed algorithm yields visually superior images compared to several of the recently reported POCS deblocking algorithms for the class of images considered.
机译:在本文中,提出了一种新颖的凸集投影(POCS)方法,用于抑制包含均匀区域的压缩图像中的阻塞和振铃伪影。利用图像区域的均匀性,引入了一个新的凸平滑约束集族。这组约束条件允许在保留图像边缘的同时在图像的不同区域进行不同程度的平滑处理。使用模糊c均值算法对区域进行分割,该算法可以使模糊像素保持未分类状态。在JPEG压缩图像上的实验结果表明,与最近考虑的图像类别的POCS解块算法相比,该算法产生的视觉效果更好。

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