Aiming at the problems of image fusion in spatial domain, such as the extraction of different image sources and difficulty in selecting fusion weights, a new spatial domain image fusion algorithm is proposed. Using the basic principle of matrix similarity, the infrared image matrix is diagonally transformed, the visible light image matrix is mapped on the main eigenvectors, the weighted fusion method is used to process the eigenvalue matrix, and the fusion matrix is diagonalized inversely transformed and reconstructed Fusion image. Experimental results show that while the algorithm fully retains the effective information of the source image, the overall grayscale of the fused image has been significantly improved, and it has a good image quality evaluation index and better visual effects.
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