Hyperspectral image noise reduction based on rank-1 tensor decomposition
By Xian Guo, Xin Huang, Liangpei Zhang, Lefei Zhang. 2013
112 citations recorded by the source corpus.
Subfields: Computational Mechanics, Computer Vision and Pattern Recognition, Media Technology
View Paper: https://www.semanticscholar.org/paper/b79b0b61b842cc043be29eee07e6da15b4137d4b
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computational Mechanics
- Huanfeng Shen
- Hongyan Zhang
- Wei He
- Liangpei Zhang
- Lina Zhuang
- José M. Bioucas-Dias
- Pedram Ghamisi
- Behnood Rasti
In Computer Vision and Pattern Recognition
In Media Technology
- Huanfeng Shen
- Hongyan Zhang
- Wei He
- Liangpei Zhang
- José M. Bioucas-Dias
- Jocelyn Chanussot
- Lina Zhuang
- Bo Du
Citations in the corpus
- Total-Variation-Regularized Low-Rank Matrix Factorization for Hyperspectral Image Restoration (2016, methodology): “D multidimensional data cube, multidimensional Wiener filtering (MWF) [9], [10] and high-order rank-1 tensor decomposition [11], which jointly take into account the spatial spectral information, have also been adopted to denoise HSIs.”