Quantification of the impact of misregistration on the accuracy of remotely sensed change detection

Abstract

The impact of misregistration on the accuracy of change detection is quantitatively investigated using TM imagery. This simulation study focuses on two interconnected issues. First, the statistical properties of the difference images are evaluated using semivariograms when images are progressively misregistered in order to investigate the band sensitivity, temporal sensitivity, and spatial frequency sensitivity of change detection to misregistration. The ellipsoidal change detection technique is then proposed and used to progressively detect the land cover transitions at each misregistration stage for each image. The impact of misregistration on change detection is then evaluated in terms of the accuracy of change detection using the output from the ellipsoidal change detector.