Image registration is an essential prerequisite for multisource image fusion. To further improve the registration accuracy for long-wave infrared and visible images, a feature point descriptor construction method—edge-oriented log-Gabor descriptor is proposed. Initially, grayscale edge images are obtained by a structured random forests edge detector, which is more suitable for extracting features using multiscale and multioriented log-Gabor filters. Then, edge features are used for selecting orientation-stabilized feature points from speeded up robust feature points, and descriptors are constructed with a two-stage Gaussian weighting scheme. Finally, feature point pairs are matched by computing the difference of descriptors. Experimental results show that the proposed approach achieves better performance compared with state-of-the-art methods.