Regular Articles

Total variation-regularized weighted nuclear norm minimization for hyperspectral image mixed denoising

[+] Author Affiliations
Zhaojun Wu, Qiang Wang, Yi Shen

Harbin Institute of Technology, Department of Control Science and Engineering, Harbin 150001, China

Zhenghua Wu

China Electronics Technology Group Corporation, No. 38 Research Institute, Hefei 230088, China

J. Electron. Imaging. 25(1), 013037 (Feb 26, 2016). doi:10.1117/1.JEI.25.1.013037
History: Received July 29, 2015; Accepted January 27, 2016
Text Size: A A A

Abstract.  Many nuclear norm minimization (NNM)-based methods have been proposed for hyperspectral image (HSI) mixed denoising due to the low-rank (LR) characteristics of clean HSI. However, the NNM-based methods regularize each eigenvalue equally, which is unsuitable for the denoising problem, where each eigenvalue stands for special physical meaning and should be regularized differently. However, the NNM-based methods only exploit the high spectral correlation, while ignoring the local structure of HSI and resulting in spatial distortions. To address these problems, a total variation (TV)-regularized weighted nuclear norm minimization (TWNNM) method is proposed. To obtain the desired denoising performance, two issues are included. First, to exploit the high spectral correlation, the HSI is restricted to be LR, and different eigenvalues are minimized with different weights based on the WNNM. Second, to preserve the local structure of HSI, the TV regularization is incorporated, and the alternating direction method of multipliers is used to solve the resulting optimization problem. Both simulated and real data experiments demonstrate that the proposed TWNNM approach produces superior denoising results for the mixed noise case in comparison with several state-of-the-art denoising methods.

© 2016 SPIE and IS&T

Topics

Denoising

Citation

Zhaojun Wu ; Qiang Wang ; Zhenghua Wu and Yi Shen
"Total variation-regularized weighted nuclear norm minimization for hyperspectral image mixed denoising", J. Electron. Imaging. 25(1), 013037 (Feb 26, 2016). ; http://dx.doi.org/10.1117/1.JEI.25.1.013037


Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

PubMed Articles
Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.