High spatial resolution images available by satellites such as Ikonos, Quickbird, and WorldView-2 provide more information for remote sensing applications, such as object detection, classification, change detection, and object mapping. The presence of shadow reduces the amount of information that can be extracted and consequently makes these applications more difficult or even impossible. In this article, a shadow restoration approach for high-resolution satellite images is proposed. The approach detects the shadow area and segments the image into regions according to the land surface type. Then, shadow restoration is carried out for each region based on the degree of correspondence between shadow and neighbouring non-shadow regions. The proposed approach is applied to study areas from Ikonos and WorldView-2 satellite images. A comparison to the standard approaches for shadow restoration is performed, and an accuracy assessment is carried out by visual inspection and land-cover classification. The results show that the enhanced shadow regions using the proposed approach have better appearances and are highly compatible with their surrounding non-shadow regions. In addition, the overall accuracy is higher than those of the standard approaches.
All Science Journal Classification (ASJC) codes
- Earth and Planetary Sciences(all)