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Patch-adaptive non-local means filtering for image deblocking using a no-reference metric

机译:修补程序自适应非本地意味着使用无参考度量对图像进行解块滤波

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Annoying blocking artifacts are exhibited in images compressed by block discrete cosine transform (BDCT), primarily at low bit-rate. Many algorithms have been proposed to alleviate this degradation by removing quantization noise, under the condition that the noise magnitude is known. However, in many applications the receiver only gets the degraded image without any prior knowledge about noise distributions, in which case the usage of the existing deblocking algorithms are significantly limited. In this paper, we propose a novel patch-adaptive non-local means filter for deblocking using no side information about noise distribution. To do this work, a no-reference metric is first given to evaluate the deblocking efficiency. Then, the non-local means filter is applied block by block and the metric is used to choose the optimal filtering degree adaptively. The result of proposed deblocking algorithm is superior to conventional approaches in both subjective and objective aspects, which are supported by extensive experiments.
机译:恼人的块状伪像主要在低比特率下出现在通过块离散余弦变换(BDCT)压缩的图像中。已经提出了许多在噪声幅度已知的条件下通过去除量化噪声来减轻这种劣化的算法。然而,在许多应用中,接收器仅获得降级的图像,而没有关于噪声分布的任何先验知识,在这种情况下,现有去块算法的使用受到极大限制。在本文中,我们提出了一种新颖的补丁自适应非局部均值滤波器,用于不使用有关噪声分布的辅助信息进行解块。为了完成这项工作,首先要给出一个无参考指标来评估解块效率。然后,逐块地应用非局部均值滤波器,并且使用度量来自适应地选择最佳滤波度。提出的解块算法的结果在主观和客观方面均优于常规方法,并得到了广泛实验的支持。

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