Research on stitching technology based on enhanced images of substations

Abstract

The digital, intelligent and visual operation of substations has become a current research trend. In order to obtain allweather substation image information, this paper proposes to enhance the low-light image at night based on gamma correction, then match the enhanced image with feature points, transform the image by Fourier-Mellin transform (FM) to obtain the overlapping area; use the fast approximate nearest neighbour (FLANN) matching algorithm for coarse matching, introduce the progressive sample consensus (PROSAC) to finely filter the feature points to improve the correct rate; finally, the stitched image is weighted fusion processing to remove the stitching seam. (PROSAC) to finely filter the feature pairs to improve the correct rate; finally, the stitched images are weighted and fused to remove the stitching seams. The experimental results show that this algorithm can enhance the night image, improve the matching accuracy and meet the requirements of stitching quality.