AmirReza Shahtahmassebi, Yang Ning, WANG Ke, Nathan Moore, SHEN Zhangquan. Review of Shadow Detection and De-shadowing Methods in Remote Sensing[J]. Chinese Geographical Science, 2013, 23(4): 403-420. doi: 10.1007/s11769-013-0613-x
Citation: AmirReza Shahtahmassebi, Yang Ning, WANG Ke, Nathan Moore, SHEN Zhangquan. Review of Shadow Detection and De-shadowing Methods in Remote Sensing[J]. Chinese Geographical Science, 2013, 23(4): 403-420. doi: 10.1007/s11769-013-0613-x

Review of Shadow Detection and De-shadowing Methods in Remote Sensing

doi: 10.1007/s11769-013-0613-x
Funds:  Under the auspices of National Technology Research and Development Program of China (No. 2006BAJ05A02), National Natural Science Foundation of China (No. 31172023)
  • Received Date: 2012-09-26
  • Rev Recd Date: 2012-11-22
  • Publish Date: 2013-07-10
  • Shadow is one of the major problems in remotely sensed imagery which hampers the accuracy of information extraction and change detection. In these images, shadow is generally produced by different objects, namely, cloud, mountain and urban materials. The shadow correction process consists of two steps: detection and de-shadowing. This paper reviews a range of techniques for both steps, focusing on urban regions (urban shadows), mountainous areas (topographic shadow), cloud shadows and composite shadows. Several issues including the problems and the advantages of those algorithms are discussed. In recent years, thresholding and recovery techniques have become important for shadow detection and de-shadowing, respectively. Research on shadow correction is still an important topic, particularly for urban regions (in high spatial resolution data) and mountainous forest (in high and medium spatial resolution data). Moreover, new algorithms are needed for shadow correction, especially given the advent of new satellite images.
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Review of Shadow Detection and De-shadowing Methods in Remote Sensing

doi: 10.1007/s11769-013-0613-x
Funds:  Under the auspices of National Technology Research and Development Program of China (No. 2006BAJ05A02), National Natural Science Foundation of China (No. 31172023)

Abstract: Shadow is one of the major problems in remotely sensed imagery which hampers the accuracy of information extraction and change detection. In these images, shadow is generally produced by different objects, namely, cloud, mountain and urban materials. The shadow correction process consists of two steps: detection and de-shadowing. This paper reviews a range of techniques for both steps, focusing on urban regions (urban shadows), mountainous areas (topographic shadow), cloud shadows and composite shadows. Several issues including the problems and the advantages of those algorithms are discussed. In recent years, thresholding and recovery techniques have become important for shadow detection and de-shadowing, respectively. Research on shadow correction is still an important topic, particularly for urban regions (in high spatial resolution data) and mountainous forest (in high and medium spatial resolution data). Moreover, new algorithms are needed for shadow correction, especially given the advent of new satellite images.

AmirReza Shahtahmassebi, Yang Ning, WANG Ke, Nathan Moore, SHEN Zhangquan. Review of Shadow Detection and De-shadowing Methods in Remote Sensing[J]. Chinese Geographical Science, 2013, 23(4): 403-420. doi: 10.1007/s11769-013-0613-x
Citation: AmirReza Shahtahmassebi, Yang Ning, WANG Ke, Nathan Moore, SHEN Zhangquan. Review of Shadow Detection and De-shadowing Methods in Remote Sensing[J]. Chinese Geographical Science, 2013, 23(4): 403-420. doi: 10.1007/s11769-013-0613-x
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