Change detection for urban analysis with high-resolution imagery: homomorphic filtering and morphological operation approach

In these days, the demand on methodologies and processing schemes for urban application or analysis using high spatial resolution imagery is increasing. In fact, most methodologies for intermediate or coarse spatial resolution imagery can also be applied for high-resolution one, and some processing methods among them show practical usefulness over those imagery data. In use of high spatial resolution imagery, change detection based on accurate extraction of target features of interests in a certain region including complex urban area or inaccessible area is of importance. For this change detection approach, two processing techniques such as homomorphic filtering and morphological operations are considered in this study. After applying other basic image rectification processing, homomorphic filtering which combines non-linear mapping function and spatial frequency filtering is helpful to reveal distinct characteristics for some complicated and multi-associated features on high spatial resolution imagery, and then morphological operations are fast and efficient processing method to detect change with homomorphic filtered and multi-temporal imagery datasets. As a result, this approach with both techniques is thought to be one of the applicable schemes for the change detection problem with high spatial resolution imagery, in the aspects of increased accuracy and automatic extraction of target features.