The current dual-mode infrared image lacks the selection and combination basis of each element when constructing the fusion method, and the fusion model cannot dynamically adjust for the image difference feature, resulting in poor fusion effect. Aiming at the above problems, referring to the multi-parameters of biological characters, this paper proposes infrared intensity and polarization image mimicry fusion based on the combination of variable elements and matrix theory. Firstly, the fusion model was divided into four parts: fusion algorithm, fusion rule, fusion parameter and fusion structure. The single mapping relationship between different parts and the difference of image feature fusion is established. Secondly, using the imaginary transformation idea, the imaginary transformation fusion method was established, and the necessary four parts of the fusion process are combined to derive a new fusion algorithm. Finally, it used the different source images with different features to verify the proposed mimetic fusion algorithm. Experimental results show that when the image difference features are different, the fusion method was more suitable for deriving image features, so as to achieve active selection and adjustment of the fusion algorithm. The different features in the fusion image can be effectively combined, and the visual effect of the original image is significantly improved.
Infrared intensity and polarization image mimicry fusion based on the combination of variable elements and matrix theory
First published at:Dec 01, 2018
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Supported by National Natural Science Foundation of China (61672472, 61702465), North University of China Science Research Fund Project (XJJ2016024), and Key Laboratory of Electronic Test Technology of North University of China Open Fund Support Project (ZDSYSJ2015005)
Get Citation: Lv Sheng, Yang Fengbao, Ji Linna, et al. Infrared intensity and polarization image mimicry fusion based on the combination of variable elements and matrix theory[J]. Opto-Electronic Engineering, 2018, 45(12): 180188.