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Hyperspectral Unmixing

Hyperspectral Unmixing is a procedure that decomposes the measured pixel spectrum of hyperspectral data into a collection of constituent spectral signatures (or endmembers) and a set of corresponding fractional abundances. Hyperspectral Unmixing techniques have been widely used for a variety of applications, such as mineral mapping and land-cover change detection.

Source: An Augmented Linear Mixing Model to Address Spectral Variability for Hyperspectral Unmixing

Papers

Showing 7180 of 113 papers

TitleStatusHype
SpACNN-LDVAE: Spatial Attention Convolutional Latent Dirichlet Variational Autoencoder for Hyperspectral Pixel Unmixing0
Spectral Unmixing Comparison with Sparse, Iterative and Mixed Integer Programming Models0
Spectral Unmixing of Hyperspectral Images Based on Block Sparse Structure0
Spectral Unmixing via Data-guided Sparsity0
SSCU-Net: Spatial-Spectral Collaborative Unmixing Network for Hyperspectral Images0
Improving Autoencoder Training Performance for Hyperspectral Unmixing with Network Reinitialisation0
Structured Sparse Method for Hyperspectral Unmixing0
Successive Projection Algorithm Robust to Outliers0
Superpixel Based Graph Laplacian Regularization for Sparse Hyperspectral Unmixing0
Tech Report: A Fast Multiscale Spatial Regularization for Sparse Hyperspectral Unmixing0
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