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A Modified Neighborhood Similar Pixel Interpolator Approach for Removing Thick Clouds in Landsat Images

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Thick cloud contaminations in Landsat images limit their regular usage for land applications. Based on the assumption that the neighboring spectral-similar pixels outside cloudy patches have similar temporal change patterns to the cloudy pixels, this paper presents an improved neighborhood similar pixel interpolator (NSPI) approach to build a cloud-free imagery. NSPI approach was originally developed and tested for filling gaps due to the Landsat ETM+ Scan Line Corrector (SLC)-off problem. Both simulated and real cloudy images were used to evaluate the performance of the proposed method. The results show that NSPI approach can restore the reflectance of cloud-contaminated images with fewer artifact edge effects comparing to a contextual multiple linear prediction (CMLP) method. The reflectance restored by NSPI approach is more accurate especially when the cloud-free auxiliary image and cloudy image are acquired from different seasons and have different spectral characteristics.
Xiaolin Zhu , Feng Gao , Desheng Liu , Jin Chen
USDA Scientist Submission
IEEE Geoscience and Remote Sensing Letters 2012 5 v.9 no.3
Journal Articles, USDA Authors, Peer-Reviewed
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