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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 4150 of 113 papers

TitleStatusHype
Towards Robust Hyperspectral Unmixing: Mixed Noise Modeling and Image-Domain RegularizationCode0
Variable-Wise Diagonal Preconditioning for Primal-Dual Splitting: Design and Applications0
A Multibranch Convolutional Neural Network for Hyperspectral Unmixing0
A consistent and flexible framework for deep matrix factorizations0
Hyperspectral Unmixing Based on Nonnegative Matrix Factorization: A Comprehensive Review0
Fast and Structured Block-Term Tensor Decomposition For Hyperspectral Unmixing0
GAUSS: Guided Encoder-Decoder Architecture for Hyperspectral Unmixing with Spatial Smoothness0
Spectral Unmixing of Hyperspectral Images Based on Block Sparse Structure0
SSCU-Net: Spatial-Spectral Collaborative Unmixing Network for Hyperspectral Images0
Deep Deterministic Independent Component Analysis for Hyperspectral UnmixingCode0
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