Robust CCD and IR Image Registration Using Gradient-Based Statistical Information

Abstract

This letter presents a robust similarity measure for registering charged-couple device (CCD) and infrared (IR) images. The measure is based on the entropy obtained from a 3-D joint histogram incorporating edginess and modified generalized gradient vector flow (GGVF). To make a reliable mapping relationship between the edge regions of two images, the concept of edginess was adopted so registration performance would be affected mainly by gradient existences rather than their magnitudes. In addition, by adopting the GGVF, we relaxed a narrow capture range problem in conventional gradient-based measures. Experimental results showed that the proposed measure performs more robustly than existing measures.