基于投影的稀疏表示与非局部正则化图像复原方法

提出一种基于投影的稀疏表示与非局部正则化相结合的图像去模糊、去噪图像复原方法.该方法结合了自适应构造字典的稀疏表示与非局部总变差，提出的正则化模型分解为三个投影子问题进行求解以提高求解效率.实验结果表明，本文所提出的图像复原方法能够有效地保持原图像的纹理细节信息，对于不同程度的退化图像上均有较好的复原结果，在视觉效果和客观评价指标上均优于相比较的现有方法.

Projection-Based Image Restoration via Sparse Representation and Nonlocal Regularization

This paper proposes a projection based sparse representation and nonlocal regularization deblurring and denoising image restoration algorithm.The algorithm combines sparse representation via adaptive learned dictionary and nonlocal total variation,and the proposed regularization model is divided into three projection sub problems to solve to improve the efficiency.Experimental results show that the proposed algorithm can preserve the detail information effectively,and have nice restoration results for images with different degree of degradation.The proposed algorithm achieves improvement on both visual appearance and objective indices compared with state-of-the-art methods.