Neural network-based multisensor image fusion algorithm

Article type: Research Article

Authors: Wang, Liang

Affiliations: Department of Computer Science, Sichuan Top IT Vocational Institute, Chengdu, Sichuan 611743, China | E-mail: 161849015@masu.edu.cn

Correspondence: [*] Corresponding author: Department of Computer Science, Sichuan Top IT Vocational Institute, Chengdu, Sichuan 611743, China. E-mail: 161849015@masu.edu.cn.

Abstract: Aiming at the problems of high mean square error and low fusion efficiency of existing fusion algorithms, a neural network-based multi-sensor image fusion algorithm is proposed. The fusion algorithm based on depth-separable convolution neural network (CNN) is determined by analyzing the quality evaluation and fusion methods of multi-sensor images, and summarizing the fusion rules. It is found that the integrity of image information acquisition is 97%, the mean square error is 4, and the fusion time is 2 s. Therefore, the algorithm has a good image fusion effect.

Keywords: Neural network, multisensor image fusion, image fusion algorithm

DOI: 10.3233/JCM-226532

Journal: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 1, pp. 297-309, 2023