Registration algorithm of multispectral images based on cross cumulative residual entropy

In order to solve the problem that classical mutual information images registration may lead to local extremum, a new matching algorithm combining the bilateral filter and cross accumulated residual entropy combination was proposed in multispectral image registration. In this algorithm, firstly, according to multispectral images characteristics, bilateral filter edge extraction algorithm was put forward based on the probability density. Secondly, cross cumulative residual entropy(CCRE) was used as the similarity measure to match the reference images and transformed images effectively. Bilateral filter is an edge-preserving and noise reducing smoothing filter, and CCRE is more general than Shannon Entropy. This function can effectively avoid the emergence of the local extremum, overcome noise influence on the the local extremum. Experimental results proved that the registration had good robustness, the effect was obvious.