A modified neighborhood similar pixel interpolator approach for removing thick clouds in landsat images

Xiaolin Zhu, Feng Gao, Desheng Liu, Jin Chen

Research output: Journal article publicationJournal articleAcademic researchpeer-review

89 Citations (Scopus)


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.
Original languageEnglish
Article number6095313
Pages (from-to)521-525
Number of pages5
JournalIEEE Geoscience and Remote Sensing Letters
Issue number3
Publication statusPublished - 1 Jan 2012
Externally publishedYes


  • Cloud removal
  • image processing
  • image restoration
  • Landsat

ASJC Scopus subject areas

  • Geotechnical Engineering and Engineering Geology
  • Electrical and Electronic Engineering

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