Visible and Infrared Image Matching Algorithm Based on Edge Image and SURF Features

Due to prominent distributional variations of grayscale between visible and infrared images,traditional matching methods based on grayscale information show obvious deficiency on these two kinds of image matching.Combining with the characteristics of these two kinds of images,an image matching algorithm based on edge image and SURF features is proposed.Firstly,we respectively extract edge images from the original images by adopting improved cubic b-spline.And secondly,we extract the SURF features from the edges of both images,then the ratio of the closest neighbor and second closest neighbor is used in the features matching.Finally,the RANSAC algorithm is applied to remove false matching points.The experiment results show that the proposed method is better than the Canny and SURF method in the correct matching probability,and the validity of matching method proposed is proved.