Night-vision Image Fusion Based on Intensity Transformation and Two-scale Decomposition

Haoran ZHU; Yunqing LIU; Wenying ZHANG

doi:10.11999/JEIT180407

Volume 41 Issue 3

Mar. 2019

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Article Navigation > Journal of Electronics & Information Technology > 2019 > 41(3): 640-648

Haoran ZHU, Yunqing LIU, Wenying ZHANG. Night-vision Image Fusion Based on Intensity Transformation and Two-scale Decomposition[J]. Journal of Electronics & Information Technology, 2019, 41(3): 640-648. doi: 10.11999/JEIT180407

Citation:

Haoran ZHU, Yunqing LIU, Wenying ZHANG. Night-vision Image Fusion Based on Intensity Transformation and Two-scale Decomposition[J]. Journal of Electronics & Information Technology, 2019, 41(3): 640-648. doi: 10.11999/JEIT180407

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Night-vision Image Fusion Based on Intensity Transformation and Two-scale Decomposition

doi: 10.11999/JEIT180407

Haoran ZHU¹,
Yunqing LIU^{1
,
,},
Wenying ZHANG^{2, 3}

1.
School of Electronics and Information Engineering, Changchun University of Science and Technology, Changchun 130022, China
2.
Photoelectric Engineering College, Changchun University of Science and Technology, Changchun 130022, China
3.
Academy of Opto-electronics, Chinese Academy of Sciences, Beijing 100094, China

Received Date: 2017-05-02
Rev Recd Date: 2018-10-18

Available Online: 2018-10-31

Publish Date: 2019-03-01

Abstract

Abstract

In order to achieve more suitable night vision fusion images for human perception, a novel night-vision image fusion algorithm is proposed based on intensity transformation and two-scale decomposition. Firstly, the pixel value from the infrared image is used as the exponential factor to achieve intensity transformation of the visible image, so that the task of infrared-visible image fusion can be transformed into the merging of homogeneous images. Secondly, the enhanced result and the original visible image are decomposed into base and detail layers through a simple average filter. Thirdly, the detail layers are fused by the visual weight maps. Finally, the fused image is reconstructed by synthesizing these results. The fused image is more suitable for the visual perception, because the proposed method presents the result in the visual spectrum band. Experimental results show that the proposed method outperforms obviously the other five methods. In addition, the computation time of the proposed method is less than 0.2 s, which meet the real-time requirements. In the fused result, the details of the background are clear while the objects with high temperature variance are highlighted as well.
- Image fusion,
- Intensity transformation,
- Two-scale decomposition,
- Visual saliency detection

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References(20)

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