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Deblocking of block-transform compressed images using weighted sums of symmetrically aligned pixels

机译:使用对称对齐像素的加权和对块变换压缩图像进行解块

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A new class of related algorithms for deblocking block-transform compressed images and video sequences is proposed in this paper. The algorithms apply weighted sums on pixel quartets, which are symmetrically aligned with respect to block boundaries. The basic weights, which are aimed at very low bit-rate images, are obtained from a two-dimensional function which obeys predefined constraints. Using these weights on images compressed at higher bit rates produces a deblocked image which contains blurred "false" edges near real edges. We refer to this phenomenon as the ghosting effect. In order to prevent its occurrences, the weights of pixels, which belong to nonmonotone areas, are modified by dividing each pixel's weight by a predefined factor called a grade. This scheme is referred to as weight adaptation by grading (WABG). Better deblocking of monotone areas is achieved by applying three iterations of the WABG scheme on such areas followed by a fourth iteration which is applied on the rest of the image. We refer to this scheme as deblocking frames of variable size (DFOVS). DFOVS automatically adapts itself to the activity of each block. This new class of algorithms produces very good subjective results and PSNR results which are competitive relative to available state-of-the-art methods.
机译:提出了一种新的相关算法,用于对块变换的压缩图像和视频序列进行解块。该算法将加权和应用于像素四重奏,像素四重奏相对于块边界对称对齐。从遵循预定义约束的二维函数获得针对极低比特率图像的基本权重。在以较高比特率压缩的图像上使用这些权重可生成解块图像,该图像包含接近真实边缘的模糊“假”边缘。我们将此现象称为重影效应。为了防止其发生,通过将每个像素的权重除以称为等级的预定义因子,可以修改属于非单调区域的像素的权重。该方案被称为通过分级的加权自适应(WABG)。通过在此类区域上应用WABG方案的三个迭代,然后在图像的其余部分上应用第四迭代,可以更好地对单调区域进行解块。我们将此方案称为可变大小的解块帧(DFOVS)。 DFOVS会自动适应每个块的活动。这类新算法可产生非常好的主观结果和PSNR结果,相对于可用的最新技术而言,这些结果具有竞争力。

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