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中文摘要：
本文首先研究设计出结构自适应的各向异性数字滤波器，同时导出广义各向异性MRF（Markov Random Field）图像模型．它继承了各向异性数字滤波器的滤波性能，是对双边全变差模型以及经典MRF模型的有效改进．随后，提出各向异性模型驱动的联合估计亚像素运动和高分辨率图像的变分超分辨率重建算法．实验结果显示，本文算法具有更优的噪声抑制和边缘保持性能．
英文摘要：
A variational super-resolution reconstruction method is proposed. First of all, a kind of structure-adaptive anisotropic filter is designed based on the recently reported bilateral filtering. It is not only edge-preserving but also comer-preserving. Then, an anlsotropic Markov random field（MRF）model is deduced, which is the improvement of both the classical MRF and bilateral total variation image models. Driven by the anisotropic MRF model, an edge-enhancing super-resolution algorithm is subse- quently proposed, simultaneously estimating the high resolution image and the sub-pixel motion among low-resolution frames. The half-quadratic regularization approach and steepest descent are exploited to solve the corresponding minimization functional. Experiment results demonstrate the effectiveness of the proposed approach, both in the visual effect and the peak signal to noise ratio （PSNR） value.
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