Method for multispectral images denoising based on tensor-singular value decomposition
| Autor: | Xianggan Zhang, Wenjia Zeng, Yechao Bai |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Computer science
Noise reduction Multispectral image Matrix norm 010103 numerical & computational mathematics 02 engineering and technology 01 natural sciences Measure (mathematics) symbols.namesake Fourier transform Dimension (vector space) Tensor (intrinsic definition) Singular value decomposition 0202 electrical engineering electronic engineering information engineering symbols General Earth and Planetary Sciences 020201 artificial intelligence & image processing 0101 mathematics Algorithm |
| Zdroj: | Journal of Applied Remote Sensing. 11:1 |
| ISSN: | 1931-3195 |
| DOI: | 10.1117/1.jrs.11.035019 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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