Pseudo Color Fusion of Infrared and Visible Images Based on the Rattlesnake Vision Imaging System

Image fusion is a key technology in the field of digital image processing. In the present study, an effect-based pseudo color fusion model of infrared and visible images based on the rattlesnake vision imaging system (the rattlesnake bimodal cell fusion mechanism and the visual receptive field model) is proposed. The innovation point of the proposed model lies in the following three features: first, the introduction of a simple mathematical model of the visual receptive field reduce computational complexity; second, the enhanced image is obtained by extracting the common information and unique information of source images, which improves fusion image quality; and third, the Waxman typical fusion structure is improved for the pseudo color image fusion model. The performance of the image fusion model is verified through comparative experiments. In the subjective visual evaluation, we find that the color of the fusion image obtained through the proposed model is natural and can highlight the target and scene details. In the objective quantitative evaluation, we observe that the best values on the four indicators, namely standard deviation, average gradient, entropy, and spatial frequency, accounts for 90%, 100%, 90%, and 100%, respectively, indicating that the fusion image exhibits superior contrast, image clarity, information content, and overall activity. Experimental results reveal that the performance of the proposed model is superior to that of other models and thus verified the validity and reliability of the model.