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

被引：157

作者：

Zhu, Xiaolin ^{[1
,2
]}

Gao, Feng ^{[4
]}

Liu, Desheng ^{[2
,3
]}

Chen, Jin ^{[1
]}

机构：

[1] Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China

[2] Ohio State Univ, Dept Geog, Columbus, OH 43210 USA

[3] Ohio State Univ, Dept Stat, Columbus, OH 43210 USA

[4] ARS, Hydrol & Remote Sensing Lab, USDA, Beltsville, MD 20705 USA

来源：

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS | 2012年 / 9卷 / 03期

基金：

美国国家科学基金会;

关键词：

Cloud removal; image processing; image restoration; Landsat;

D O I：

10.1109/LGRS.2011.2173290

中图分类号：

P3 [地球物理学]; P59 [地球化学];

学科分类号：

0708 ; 070902 ;

摘要：

Thick-cloud contamination is a common problem in Landsat images, which limits their utilities in various land surface studies. This letter presents a new method for removing thick clouds based on a modified neighborhood similar pixel interpolator (NSPI) approach that was originally developed for filling gaps due to the Landsat ETM+ Scan Line Corrector (SLC)-off problem. The performance of the proposed method was evaluated with both simulated and real cloudy images and compared with that of a contextual multiple linear prediction (CMLP) method. The results show that the modified NSPI approach can greatly reduce the edge effects by CMLP. The reflectance restored by the modified NSPI approach is more accurate than that by CMLP, especially when the cloud-free auxiliary and cloudy images are acquired from different seasons and have different spectral characteristics.

引用

页码：521 / 525

页数：5

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