Feature Point Matching Method Based on Consistent Edge Structures for Infrared and Visible Images

Infrared and visible image match is an important research topic in the field of multi-modality image processing. Due to the difference of image contents like pixel intensities and gradients caused by disparate spectrums, it is a great challenge for infrared and visible image match in terms of the detection repeatability and the matching accuracy. To improve the matching performance, a feature detection and description method based on consistent edge structures of images (DDCE) is proposed in this paper. First, consistent edge structures are detected to obtain similar contents of infrared and visible images. Second, common feature points of infrared and visible images are extracted based on the consistent edge structures. Third, feature descriptions are established according to the edge structure attributes including edge length and edge orientation. Lastly, feature correspondences are calculated according to the distance of feature descriptions. Due to the utilization of consistent edge structures of infrared and visible images, the proposed DDCE method can improve the detection repeatability and the matching accuracy. DDCE is evaluated on two public datasets and are compared with several state-of-the-art methods. Experimental results demonstrate that DDCE can achieve superior performance against other methods for infrared and visible image match.