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Hyperspectral Image Denoising with Cubic Total Variation Model : Volume I-7, Issue 1 (17/07/2012)

By Zhang, H.

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Book Id: WPLBN0004013732
Format Type: PDF Article :
File Size: Pages 4
Reproduction Date: 2015

Title: Hyperspectral Image Denoising with Cubic Total Variation Model : Volume I-7, Issue 1 (17/07/2012)  
Author: Zhang, H.
Volume: Vol. I-7, Issue 1
Language: English
Subject: Science, Isprs, Annals
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Zhang, H. (2012). Hyperspectral Image Denoising with Cubic Total Variation Model : Volume I-7, Issue 1 (17/07/2012). Retrieved from

Description: The State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, Hubei, China. Image noise is generated unavoidably in the hyperspectral image acquision process and has a negative effect on subsequent image analysis. Therefore, it is necessary to perform image denoising for hyperspectral images. This paper proposes a cubic total variation (CTV) model by combining the 2-D total variation model for spatial domain with the 1-D total variation model for spectral domain, and then applies the termed CTV model to hyperspectral image denoising. The augmented Lagrangian method is utilized to improve the speed of solution of the desired hyperspectral image. The experimental results suggest that the proposed method can achieve competitive image quality.



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