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Journal of Applied Remote Sensing • new

Combining interior and exterior characteristics for remote sensing image denoising
Author(s): Ni Peng; Shujin Sun; Runsheng Wang; Ping Zhong
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Paper Abstract

Remote sensing image denoising faces many challenges since a remote sensing image usually covers a wide area and thus contains complex contents. Using the patch-based statistical characteristics is a flexible method to improve the denoising performance. There are usually two kinds of statistical characteristics available: interior and exterior characteristics. Different statistical characteristics have their own strengths to restore specific image contents. Combining different statistical characteristics to use their strengths together may have the potential to improve denoising results. This work proposes a method combining statistical characteristics to adaptively select statistical characteristics for different image contents. The proposed approach is implemented through a new characteristics selection criterion learned over training data. Moreover, with the proposed combination method, this work develops a denoising algorithm for remote sensing images. Experimental results show that our method can make full use of the advantages of interior and exterior characteristics for different image contents and thus improve the denoising performance.

Paper Details

Date Published: 31 May 2016
PDF: 26 pages
J. Appl. Remote Sens. 10(2) 025016 doi: 10.1117/1.JRS.10.025016
Published in: Journal of Applied Remote Sensing Volume 10, Issue 2
Show Author Affiliations
Ni Peng, National Univ. of Defense Technology (China)
Shujin Sun, National Univ. of Defense Technology (China)
Runsheng Wang, National Univ. of Defense Technology (China)
Ping Zhong, National Univ. of Defense Technology (China)


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