Local Dominant Orientation Based Mutual Information for Multisensor Template Matching

Abstract

Mutual information (MI) has been very successful in multisensor or multimodal image matching. However, it may lead to mismatching due to lack of spacial information. In this paper, based on a local dominant orientation (LDO), which is a stable nature among images of different sensors and is widely used in the relative rotation estimation, an improved MI for multisensor images matching is proposed. Firstly, the frequently used intensity images are converted to a LDO represented form, where the LDO for each pixel is calculated by cumulating the surrounding gradient vectors within a disk like region. Next, we introduce a simple clustering to cluster each transformed image, thus the joint histogram of MI in the matching stage can be reduced significantly, and hence the computations, memory consumption. Our approach is evaluated by 10 groups of multisensor images, and the results have demonstrated its outstanding performances.