Infrared/Visible Image Matching Algorithm Based on NSCT and DAISY
Interest point detection and matching are basic computer vision tasks. This paper uses the NonSubsampled Contourlet Transform (NSCT) detector combined with a DAISY descriptor to develop a robust interest point matching algorithm for infrared/visible images. The NSCT-based detector is very efficient in detecting relevant image features that have good localization and rich geometric information. Once interest points have been extracted, a fast DAISY descriptor can be computed to represent these points, and finally we match them by comparing their descriptors using the Euclidean Distance (ED) and the RANdom SAmple Consensus (RANSAC). The experiment results illustrate that the proposed algorithm has certain robustness for infrared/visible image feature matching.
NSCT interest point detection DAISY ED RANSAC.
Sasa Wang Zhenbing hao Ping Yu Zejing Guang
School of Electrical and Electronic Engineering, North China Electric Power University Baoding, China
国际会议
2011 4th International Congress on Image and Signal Processing(第四届图像与信号处理国际学术会议 CISP 2011)
上海
英文
2105-2108
2011-10-15（万方平台首次上网日期，不代表论文的发表时间）