Infrared and Visible Image Fusion Algorithm Based on Regional Similarity

To address the problems of local blur and incomplete background information in the traditional fusion algorithm of infrared and visible images, a new fusion algorithm is proposed in this paper. The edge detection operator was used to extract the image contour, and weighted fusion based on energy was also executed. The similarity between regions was used to extract the signal domain. Finally, image fusion is performed according to the over-signal strength. To verify the correctness of the algorithm, a comparative test was conducted and a quantitative analysis was performed using three parameters: standard deviation, information entropy, and average gradient. Compared with the traditional weighted average algorithm, the standard deviation of this method was up to 106.3 %. The test results confirmed that the fusion method proposed in this study has a better fusion effect and practical value.