An unsupervised change detection technique robust to registration noise

In this paper, we propose a technique for reducing the effects of registration noise in unsupervised change-detection. Such a technique represents a significant improvement of the approach proposed in L. Bruzzone et al. (2001). It is composed of three main phases. The first phase aims at identifying the direction of the residual misregistration between multitemporal images by an iterative procedure applied to the 2-dimensional spatial domain of images. The second phase, given the direction of misregistration detected in the previous one, estimates the distribution of registration noise in the module-phase (M-P) domain of the difference image. Finally, the third phase generates the change-detection map by taking into account the estimated registration-noise distribution. Experimental results, obtained on a real multitemporal data set, confirm the effectiveness of the proposed approach.