中文摘要：

基于块的图像处理方法将欧氏距离作为相似块的评判标准，无法很好地反映块之间的结构性，导致重构图像存在不同程度的块效应。该文根据基于块的维纳滤波器能够充分利用图像块冗余度的特点，结合块效应的空间分布特征，提出一种改进的基于块局部最优维纳滤波的图像重构算法。首先，该算法通过对图像高频部分稀疏采样，将块效应限定在块与块的交界处，然后将图像分成块边界区域和块中心区域，利用几何结构相似和亮度相似的图像块确定滤波参数，进而平滑块效应。实验结果表明，该算法可以有效抑制重构过程中的块效应，且对于细节丰富的图像，重构效果的提升更加明显。

英文摘要：

Generally, the patch-based image processing methods use Euclidean Distance as the criterion of similar patches, which is impossible to fully reveal the patch structures and brings about the existence of blocking effect in the reconstructed image. In this paper, combining with the patch redundancy exploitation of the patch-based Wiener filter and the spatial distribution of blocking effect, an improved image reconstruction algorithm based on the patch-based locally optimal Wiener filtering is proposed. Firstly, the high-frequency part of the image is sampled sparsely, restricting the blocking effect to the border of adjacent blocks. Then the image is separately divided into two parts： the marginal region of blocks and the central region of blocks, and photometrically and geometrically similar patches are further utilized to determine the filtering parameters, which contribute to the smoothness of blocking region. As is shown by the experimental results, the proposed algorithm is able to efficiently reduce the blocking effect produced in the reconstruction and achieve a much better performance in terms of the images with rich textures.