A Novel Approach Extracting Extreme Points Combining Multidirection Phase Superposition and Weighted Moment Diagram for Matching Multi-Modal Images

Abstract

This article proposed the novel approach of multimodel image matching based on the feature integration of multidirectional phase superposition and weighted moment diagrams to handle the matching problem of large contrast differences, lots of noises, and nonlinear radiometric distortion between an image pair. There are three steps for this method. First, the presented method extracted the local extreme points in multidirectional phase superposition diagram and the edge extreme points in the weighted moment diagram. Then, the characteristic descriptor was produced. Finally, angle-assisted difference measurement was put forward to handle the problem of angle reverse. In the collected dataset, this method was experimentally compared with RIFT, CoFSM, and HAPCG. The number of extreme points and Recall of PSMWD are higher than those of RIFT and HAPCG. In image pairs of noises, the number of correct matchings of PSMWD is about twice of HAPCG. Therefore, the proposed theory has practical importance.

Keywords

• Extreme points
• feature-based multimodal image matching
• phase congruency