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Remote SensingRemote Sensing
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29 January 2021

Correction: Zhang, G., et al. Shadow Detection and Restoration for Hyperspectral Images Based on Nonlinear Spectral Unmixing. Remote Sensing 2020, 12, 3985

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Department of Photogrammetry and Remote Sensing, German Aerospace Center (DLR), 88234 Wessling, Germany
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Author to whom correspondence should be addressed.
This article belongs to the Special Issue Spectral Unmixing of Hyperspectral Remote Sensing Imagery
The authors would like to make the following correction of [1]:

Text Correction

In the original article, there was a mistake in Equation (8) as published. There should not be the third term i = 1 p 1 j = i + 1 p a l , i · a l , j · e l , i · e l , j , as it is a repetition of the second term in Equation (7). The corrected Equation (8) appears below.
x = i = 1 p a l , i · e l , i + i = 1 p a s , i · e s , i
The authors apologize for any inconvenience caused and state that the scientific conclusions are unaffected. The original article has been updated.
In the original article, there was a mistake in Equations (9)–(11) as published. The underline symbol “_” should not be used to represent the subscript, because it is not a unified mathematical expression compared with other equations in the paper.
The corrected Equation (9) appears below.
x restore = i = 1 p ( a l , i + a s , i ) · e l , i + i = 1 p 1 j = i + 1 p a l , i · a l , j · e l , i · e l , j
The corrected Equation (10) appears below.
x = i = 1 p a s , i · e s , i
The corrected Equation (11) appears below.
x = i = 1 p a l , i · e l , i + i = 1 p 1 j = i + 1 p a l , i · a l , j · e l , i · e l , j
The authors apologize for any inconvenience caused and state that the scientific conclusions are unaffected. The original article has been updated.

Acknowledgments

The authors would like to thank Paul Scheunders for pointing out the typos.

Conflicts of Interest

The authors declare no conflict of interest.

Reference

  1. Zhang, G.; Cerra, D.; Müller, R. Shadow Detection and Restoration for Hyperspectral Images Based on Nonlinear Spectral Unmixing. Remote Sens. 2020, 12, 3985. [Google Scholar] [CrossRef]
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