Infrared Technology, Volume. 42, Issue 11, 1061(2020)

Infrared and Visible Image Fusion Based on BEMD and Improved Visual Saliency

Xiaorong CUI*, Tao SHEN, Jianlu HUANG, and Di WANG
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  • [in Chinese]
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    Aiming at the problems of low target contrast and insufficiently clear images in the process of visual saliency fusion, this paper proposes an improved frequency Tuned algorithm based on bi-dimensional empirical mode decomposition (BEMD). First, the strong points and contour information of the infrared image captured by BEMD is used to guide the generation of saliency maps of the infrared image. Then, the visible image and the enhanced infrared image are subjected to a non-subsampled contourlet transform(NSCT). The saliency map-guided fusion rule is used for the low-frequency part. The high-frequency part is used to set the area energy to be large and rely on the threshold value rules. Finally, the inverse NSCT transform is used to generate a fused image and subjective visual and objective index evaluations are performed to it. The results show that the method in this paper achieves a multi-level and adaptive analysis of the original image, and achieves good vision compared to the contrast methods.


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    CUI Xiaorong, SHEN Tao, HUANG Jianlu, WANG Di. Infrared and Visible Image Fusion Based on BEMD and Improved Visual Saliency[J]. Infrared Technology, 2020, 42(11): 1061

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    Paper Information


    Received: Jan. 23, 2020

    Accepted: --

    Published Online: Jan. 11, 2021

    The Author Email: Xiaorong CUI (