High quality multi-focus image fusion using self-similarity and depth information

被引:78
作者
Guo, Di [1 ]
Yan, Jingwen [2 ]
Qu, Xiaobo [3 ]
机构
[1] Xiamen Univ Technol, Fujian Prov Univ Key Lab Internet Things Applicat, Sch Comp & Informat Engn, Xiamen 361005, Peoples R China
[2] Shantou Univ, Dept Elect Engn, Guangdong Prov Key Lab Digital Signal & Image Pro, Shantou 515063, Peoples R China
[3] Xiamen Univ, Dept Elect Sci, Fujian Prov Key Lab Plasma & Magnet Resonance Res, Xiamen 361005, Peoples R China
关键词
Image fusion; Self-similarity; Adaptive; Depth; TRANSFORM; CRITERION; DOMAIN;
D O I
10.1016/j.optcom.2014.10.031
中图分类号
O43 [光学];
学科分类号
070207 [光学];
摘要
Due to the limited depth of field in a camera, some imaging objects will be blurred if they are located far from the focus plane and the other objects on the plane will be clear. Multi-focus image fusion synthesizes a sharp image from multiple partially focused images. However, traditional fused images usually suffer from blurring effects and pixel distortions. In this paper, we explore two unique characteristics of multi-focus images: (1) The self-similarity of a single image and the shared similarity among multiple source images; (2) The distances from object to focal plane. The former characteristic is used to identify image structure-driven regions while the latter refine the image clarity by automatically estimating depth information of blurred images. Experimental results demonstrate that the proposed method outperforms the state-of-the-art fusion methods on image quality and objective fusion criteria. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:138 / 144
页数:7
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