Novel Measures Based on Simple Schur Concave Function for Image Registration
Jinbao Yang · Dianzi xuebao · 2008
When the influence of noise,interpolation and image modality is considered,the image registration method based on mutual information or normalized mutual information may cause local extrema,small convergence area,and even inaccurate registration.According to a simple Schur concave function and the definition of Jensen-Schur measure,generalized divergence measure and f information measure,six new measures were constructed.The Schur function with special concave characteristics can filter the small probability distribution caused by noise,interpolation and so on.The characters of six new measures,mutual information and normalized mutual information are analyzed and compared by applying them to rigid registration.The results of tests show that Jensen-Schur-beta and D-beta measures outperform other measures in convergence performance and noise immunity,and they are time saving in comparison with mutual information and normalized mutual information measures.