Method for multispectral images denoising based on tensor-singular value decomposition

Wenjia Zeng; Xianggan Zhang; Yechao Bai

doi:10.1117/1.JRS.11.035019

27 September 2017 Method for multispectral images denoising based on tensor-singular value decomposition

Wenjia Zeng, Xianggan Zhang, Yechao Bai

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 11, Issue 3, 035019 (September 2017). https://doi.org/10.1117/1.JRS.11.035019

Abstract

We propose a sparsity measure for third-order tensor, called all-dimension tensor nuclear norm (AD-TNN). In specific, we exploit the tensor-singular value decomposition and tensor nuclear norm (TNN), considering TNN along every dimension and then construct our AD-TNN measurement. Based on AD-TNN, we construct a model for multispectral images denoising. We also employ the alternating direction method of multipliers (ADMM) to solve our model. Experimental results show that our method outperforms all the compared methods under comprehensive quantitative performance measures.

Citation Download Citation

Wenjia Zeng, Xianggan Zhang, and Yechao Bai "Method for multispectral images denoising based on tensor-singular value decomposition," Journal of Applied Remote Sensing 11(3), 035019 (27 September 2017). https://doi.org/10.1117/1.JRS.11.035019

Received: 25 May 2017; Accepted: 31 August 2017; Published: 27 September 2017

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