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

Permanent URL:
http://handle.nal.usda.gov/10113/59900
File:
Download [PDF File]
Abstract:
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.
Author(s):
Xiaolin Zhu , Feng Gao , Desheng Liu , Jin Chen
Note:
USDA Scientist Submission
Source:
IEEE Geoscience and Remote Sensing Letters 2012 5 v.9 no.3
Language:
English
Year:
2012
Collection:
Journal Articles, USDA Authors, Peer-Reviewed
Rights:
Works produced by employees of the U.S. Government as part of their official duties are not copyrighted within the U.S. The content of this document is not copyrighted.