Laser & Optoelectronics Progress, Volume. 58, Issue 6, 610001(2021)

Infrared and Low-Light Image Fusion Based on Tetrolet and Cauchy Fuzzy Function

Cui Ziwei, Zhan Weida*, Fu Jingqi, and Wei Ranran
Author Affiliations
  • School of Electronic Information Engineering, Changchun University of Science and Technology, Changchun, Jilin 130022, China
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    In order to improve the problems of low contrast, lack of detailed information, and poor fusion effect of the fusion image, a new algorithm for infrared and low light image fusion, that is, a fusion algorithm based on Cauchy fuzzy function under Tetrolet transform, is proposed. First, the source image is decomposed into two sets of high-frequency and low-frequency coefficients by Tetrolet transform; then, a regional energy-Cauchy fuzzy function rule is proposed for the low-frequency coefficients and the regional Laplacian energy sum is used for high-frequency coefficients; finally, the inverse Tetrolet transform is used to transform the new high-frequency and low frequency coefficients into the final fusion results. Experimental results show that the proposed method has certain advantages in improving the contrast of fused images and preserving image details.

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    Cui Ziwei, Zhan Weida, Fu Jingqi, Wei Ranran. Infrared and Low-Light Image Fusion Based on Tetrolet and Cauchy Fuzzy Function[J]. Laser & Optoelectronics Progress, 2021, 58(6): 610001

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    Paper Information

    Category: Image Processing

    Received: Jun. 17, 2020

    Accepted: --

    Published Online: Mar. 11, 2021

    The Author Email: Weida Zhan (zhanweida@cust.edu.cn)

    DOI:10.3788/LOP202158.0610001

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