Analysis of spatial distribution pattern of change-detection error caused by misregistration

Misregistration between multitemporal remotely sensed images is one of the significant sources of change-detection errors. In this study, spatial distribution of change-detection errors induced by misregistration was analysed quantitatively. First, multitemporal images are registered with different misregistration values measured by root mean square error (RMSE) from 0 to 1 pixels. The image differencing method, one of the most widely used change-detection methods, is then used to detect changes. Finally, the spatial distribution pattern of change-detection errors caused by misregistration is analysed using buffering analysis based on multitemporal image edges. Experimental results indicate that the commission errors caused by misregistration values from 0 to 1 pixels are almost always within 1 pixel of the edge, regardless of image resolution. In addition, the omission errors falling within 1 pixel of the edges are about 70% for medium-resolution images. The omission errors falling within 1 or 2 pixels of the edges for high-resolution images can be as much as 50% to 60%. This work improves the understanding of spatial distribution of change-detection errors caused by misregistration and shows the relations between these errors and image edges. Moreover, it is helpful for developing new methods by combining edge and spatial information to reduce the adverse effects of misregistration on change-detection.