Abstract
ABSTRACTRemote sensing images provide a valuable source of information about the earth's surface. The presence of shadow can reduce the amount of information that can be extracted from these images. Shadow in remote sensing images is produced due to blockage of a direct light by an object. In spite of the reflectance gathered in the shadow area being weak, there is still valuable information that makes shadow restoration possible. Shadow restoration process consists of 2 main steps: detection and compensation. Various algorithms and methods have been developed to perform these 2 steps. These algorithms differ according to the objects causing shadow and types of sensor. Consequently, it is important to review the different approaches that have been employed in shadow correction research to delineate their suitability for a specific application. This article is aimed at reviewing various shadow detection and compensation techniques with their methods of evaluation, taking into consideration objects causing shadow and type of sensor used. Also, it gives discussion and recommendations to enhance the performance of existing methods.
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