提出了一种基于多引导滤波器的单幅图像超分辨率方法。首先，该方法通过大量的自然图像建立高低分辨率图像块样本训练库，并通过聚类算法将具有相似性质的高低分辨率样本块进行聚类；其次，将输入低分辨率图像进行重叠分块，并在样本库中搜索最近邻的高低分辨率样本聚类；再次，将输入低分辨率图像块作为输入图像，与样本库中最近邻的低分辨率聚类样本作为引导图像，运用本文提出的多引导滤波器计算引导滤波器的参数；最后，利用样本库中最近邻的高分辨率聚类样本和引导滤波器的参数，通过多引导滤波器就可以重构高分辨率图像。实验结果表明，本文算法不仅能很好地重构图像的高频细节，还能很好地恢复图像的纹理特征。

In this paper, a single image super-resolution method based on multi-guided filtering is proposed. First, an exemplar training database consisting of pairs of low-resolution and corresponding high-resolution image patches is constructed using many natural images. High- and low-resolution image patches with similar properties are clustered using a clustering algorithm. Next, the low-resolution input image is divided into overlapping patches, and the nearest neighbor high-and low-resolution sample cluster is searched against the exemplar training database. Then, the low-resolution input image patch is used as the new input; the nearest neighbor low-resolution clustering sample is used as the guide image. The multi- guided filter is used to calculate the parameters of the guide filter. Finally, the high-resolution images can be reconstructed with the multi-guided filter using the nearest neighbor high-resolution clustering samples and the parameters of the multi-guide in the sample bank. Experimental results show that the proposed algorithm not only reconstructs the high-frequency detail of an image, but also recovers the texture features.