Abstract
Aiming at the community security and other fields which has strict requirements on the scale of infrared / visible image fusion calculation, this paper proposes an infrared / visible image feature domain fusion algorithm. The algorithm first uses the principal component analysis (PCA) model to transform the visible light image into the corresponding feature domain, and then projects the infrared light image onto the feature domain of the visible light image, and then performs segmented fusion of its principal components in the feature domain, and finally the fusion image is reconstructed. Experimental verification: when only 95% of the principal components are used for fusion, the performance of this algorithm in parameters such as STD and MI is better than some multi-scale transformation image fusion algorithms, and it is more excellent in the presentation of feature information.
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