期刊
INFORMATION FUSION
卷 33, 期 -, 页码 100-112出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.inffus.2016.05.004
关键词
Image fusion; Multiscale decomposition; Sparse representation; Remote sensing; Medical imaging
资金
- National Natural Science Fund of China for Distinguished Young Scholars [61325007]
- National Natural Science Fund of China for International Cooperation and Exchanges [61520106001]
Pixel-level image fusion is designed to combine multiple input images into a fused image, which is expected to be more informative for human or machine perception as compared to any of the input images. Due to this advantage, pixel-level image fusion has shown notable achievements in remote sensing, medical imaging, and night vision applications. In this paper, we first provide a comprehensive survey of the state of the art pixel-level image fusion methods. Then, the existing fusion quality measures are summarized. Next, four major applications, i.e., remote sensing, medical diagnosis, surveillance, photography, and challenges in pixel-level image fusion applications are analyzed. At last, this review concludes that although various image fusion methods have been proposed, there still exist several future directions in different image fusion applications. Therefore, the researches in the image fusion field are still expected to significantly grow in the coming years. (C) 2016 Elsevier B.V. All rights reserved.
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