外文翻译原文-基于稀疏表示的多聚焦图像融合与恢复.pdf

884 IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, VOL. 59, NO. 4, APRIL 2010 Multifocus Image Fusion and Restoration With Sparse Representation Bin Yang and Shutao Li, Member, IEEE Abstract—To obtain an image with every object in focus, we al- to get all the objects focused in one image is multifocus image ways need to fuse images taken from the same view point with dif- fusion technique. In this technique, several images of a scene ferent focal settings. Multiresolution transforms, such as pyramid are captured with focus on different parts. Then, these images decomposition and wavelet, are usually used to solve this problem. In this paper, a sparse representation-based multifocus image are fused with the hope that all the objects will be in focus in fusion method is proposed. In the method, first, the source image is the resulting image [5]–[9]. represented with sparse coefficients using an overcomplete dictio- There are various methods available to implement image nary. Second, the coefficients are combined with the choose-max fusion. Basically, these methods can be categorized into two fusion rule. Finally, the fused image is reconstructed from the categories. The first category is the spatial domain-based meth- combined sparse coefficients and the dictionary. Furthermore, the proposed fusion scheme can simultaneously resolve the image ods, which directly fuse the source images into the intensity restoration and fusion problem by changing the approximate values [10]–[13]. The other category is the transformed criterion in the sparse representation algorithm. The