A robust multi-source remote-sensing image registration method based on feature matching

A robust feature based image registration method is proposed for multi-source remote-sensing images. Firstly, phase congruency transform is used to compute phase information images for removing the influence of the great differences in gray-level or contrast and to extract the control points. Then, the cross correlation function is reconstructed by Zernike moment and maximized to match the control-point pairs under rotation condition. Simultaneously, the initial feature point pairs are gained with the matching strategy of the bidirectional greatest cross correlation coefficient. Lastly, an iterative refined parameters method is used to improve the accuracy of registration. Experimental results demonstrate that this novel method can efficiently offer a reliable, robust and accurate image registration for the multi-source remote-sensing images.