Bayesian Unmixing of Hyperspectral Image Sequence With Composite Priors for Abundance and Endmember Variability

2021 ◽  
pp. 1-15
Author(s):  
Hongyi Liu ◽  
Youkang Lu ◽  
Zebin Wu ◽  
Qian Du ◽  
Jocelyn Chanussot ◽  
...  
Keyword(s):  
Hyperspectral Image ◽  
Image Sequence ◽  
Endmember Variability

scholarly journals A Hierarchical Sparsity Unmixing Method to Address Endmember Variability in Hyperspectral Image

2018 ◽  
Vol 10 (5) ◽  
pp. 738 ◽  
Author(s):  
Jinlin Zou ◽  
Jinhui Lan ◽  
Yang Shao
Keyword(s):  
Hyperspectral Image ◽  
Endmember Variability

scholarly journals Hierarchical Sparse Nonnegative Matrix Factorization for Hyperspectral Unmixing with Spectral Variability

2020 ◽  
Vol 12 (14) ◽  
pp. 2326 ◽  
Author(s):  
Tatsumi Uezato ◽  
Mathieu Fauvel ◽  
Nicolas Dobigeon
Keyword(s):  
Hyperspectral Image ◽  
Nonnegative Matrix ◽  
Hyperspectral Data ◽  
Spectral Variability ◽  
Data Set ◽  
Sparse Nonnegative Matrix Factorization ◽  
Data Driven Modeling ◽  
Endmember Variability ◽  
Conical Hull ◽  
Unmixing Model

Accounting for endmember variability is a challenging issue when unmixing hyperspectral data. This paper models the variability that is associated with each endmember as a conical hull defined by extremal pixels from the data set. These extremal pixels are considered as so-called prototypal endmember spectra that have meaningful physical interpretation. Capitalizing on this data-driven modeling, the pixels of the hyperspectral image are then described as combinations of these prototypal endmember spectra weighted by bundling coefficients and spatial abundances. The proposed unmixing model not only extracts and clusters the prototypal endmember spectra, but also estimates the abundances of each endmember. The performance of the approach is illustrated thanks to experiments conducted on simulated and real hyperspectral data and it outperforms state-of-the-art methods.

Image Sequence Enhancements Based on the Normal Component of Image Motion

1982 ◽  
Author(s):  
Larry S. Davis ◽  
Hu-chen Xie ◽  
Azriel Rosenfeld
Keyword(s):  
Normal Component ◽  
Image Sequence ◽  
Image Motion
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