4.6 Article

Multi-focus: Focused region finding and multi-scale transform for image fusion

期刊

NEUROCOMPUTING
卷 320, 期 -, 页码 157-170

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.neucom.2018.09.018

关键词

Image fusion; Meanshift; Morphological processing; Pulse coupled neural network; Nonsubsampled coutourlet transform

资金

  1. National Natural Science Foundation of China [61463052, 61365001]
  2. China Postdoctoral Science Foundation [2017M621586]

向作者/读者索取更多资源

The purpose of image fusion is to integrate useful information from multiple images and produce a more reliable image. The key problem of multi-focus image fusion is how to determine the focused regions of the source images. As an effective and excellent fusion algorithm, the focused regions in the source images should be preserved as much as possible into the fused image. To accomplish this goal, a novel multi-focus image fusion method based on a focused regions boundary finding and multi-scale transform (MST) is proposed in this paper. The Meanshift algorithm is used to determine the focused regions first. Then, an edge detection method and morphological method are used to find the boundaries of the focused regions in the source images. For the focused boundary regions, the combination of pulse coupled neural network (PCNN) and Gaussian fuzzy method is used to produce the fused boundary region in nonsubsampled contourlet transform (NSCT) domain. Finally, the fused boundary region and the focused region of the source images are fused directly. The experimental results demonstrate that the proposed algorithm can accurately determine the focused regions, and at the same time, a better fused boundary region can be obtained; this algorithm is superior to conventional methods with respect to both objective quality evaluations and visual inspection. (C) 2018 Elsevier B.V. All rights reserved.

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