Infrared Image Mosaic Method for Improving the Best Seam-line

The infrared image of a substation is significantly disturbed by noise and the texture information is unclear. Therefore, stitching traces or the ghosting phenomenon may appear in the process of stitching. To overcome these challenges, this study proposes an infrared image splicing method that improves the best seam-line. First, this method uses the SIFT algorithm to extract the image area features to achieve image registration, then introduces local weight coefficients in the overlapping area of the two images. Subsequently, morphological operations are performed on the intensity of the image color difference, which reduces the noise interference of the infrared image and improves the texture information of the energy function graph. Finally, dynamic programming is used to improve the seam-line search criteria and search for the best seam-line in the image overlapping area. The experimental results show that compared with the gradual fusion method and the best seam-line method, the average gradient, image clarity and image edge strength of the stitched image are improved, the transition of the fusion region is smoother and more natural, and the stitching trace is significantly reduced.