Robust image registration by increment sign correlation

Abstract

A novel and robust statistic as a similarity measure for robust image registration is proposed. The statistic is named as increment sign correlation because it is based on the average evaluation of incremental tendency of brightness in adjacent pixels. It is formalized to be a binary distribution or a Gaussian distribution for a large image size through statistical analysis and modeling. By utilizing the proposed statistical model, for example, we can theoretically determine a reasonable value of threshold for verification of matching. This sign correlation can also be proved to expectedly have the constant value 0.5 for any uncorrelated images to a template image, and then the property of the constancy can be utilized to analyze the high robustness for occlusion. The good performance for the case of saturation or highlight can also be proved through theoretical analysis and fundamental experiments. A basic algorithm for image scanning, search and registration over a large scene is represented with a technique for a fast version by the branch-and-bound approach. Many experimental evidences with real images are provided and discussed.