Acta Optica Sinica, Vol. 34, Issue 2, 215002 (2014)

Optical and SAR Image Registration Based on Cluster Segmentation and Mathematical Morphology

Abstract

In order to solve the problem of large difference of gray level and the difficulty of common feature extraction for optical and SAR image registration, an improved multi-model contour feature image registration method is proposed which is based on k-mean clustering segmentation and mathematical morphology. The k-mean clustering algorithm is used to get two kinds of image segmentation region, and through the mathematical morphology processing, accurate extraction of two classes of closed contour image has been realized, which can reduce the influence of the SAR image speckle noise effectively. The matching strategy of the mean and variance of torque variable distance constraint mechanism along with consistency check is bring in which aims to obtain the best match result. Through the experiment, image registration precisions of three groups reach 0.3450, 0.2163 and 0.1810, respectively, which indicates that this method is feasible and can achieve sub-pixel registration accuracy.

keywords

• consistency check
• image registration
• k-mean cluster
• machine vision
• morphology
• restriction mechanism