Journal
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE
Volume 3, Issue 3, Pages 61-85Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/MGRS.2015.2441912
Keywords
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Funding
- National Natural Science Foundation of China (NSFC) [41271376, 41422108]
- Program for Changjiang Scholars and Innovative Research Team in University [IRT1278]
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Because of sensor malfunction and poor atmospheric conditions, there is usually a great deal of missing information in optical remote sensing data, which reduces the usage rate and hinders the follow-up interpretation. In the past decades, missing information reconstruction of remote sensing data has become an active research field, and a large number of algorithms have been developed. However, to the best of our knowledge, there has not, to date, been a study that has been aimed at expatiating and summarizing the current situation. This is therefore our motivation in this review. This paper provides an introduction to the principles and theories of missing information reconstruction of remote sensing data. We classify the established and emerging algorithms into four main categories, followed by a comprehensive comparison of them from both experimental and theoretical perspectives. This paper also predicts the promising future research directions.
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