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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

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Showing 1–25 of 113 papers

TitleStatusHype
Differentiable Programming for Hyperspectral Unmixing using a Physics-based Dispersion ModelCode1
Hyperspectral Image Super-resolution via Deep Progressive Zero-centric Residual LearningCode1
Deep Hyperspectral Unmixing using Transformer NetworkCode1
UnMix-NeRF: Spectral Unmixing Meets Neural Radiance FieldsCode1
Entropic Descent Archetypal Analysis for Blind Hyperspectral UnmixingCode1
Endmember-Guided Unmixing Network (EGU-Net): A General Deep Learning Framework for Self-Supervised Hyperspectral UnmixingCode1
Integration of Physics-Based and Data-Driven Models for Hyperspectral Image UnmixingCode1
Image Processing and Machine Learning for Hyperspectral Unmixing: An Overview and the HySUPP Python PackageCode1
Nonlinear hyperspectral unmixing with robust nonnegative matrix factorizationCode0
Learning Interpretable Deep Disentangled Neural Networks for Hyperspectral UnmixingCode0
MultiHU-TD: Multifeature Hyperspectral Unmixing Based on Tensor DecompositionCode0
Low-Rank Tensor Modeling for Hyperspectral Unmixing Accounting for Spectral VariabilityCode0
A Plug-and-Play Priors Framework for Hyperspectral UnmixingCode0
Multi-Scale Convolutional Mask Network for Hyperspectral UnmixingCode0
Regularization Parameter Selection in Minimum Volume Hyperspectral UnmixingCode0
Hyperspectral Unmixing Using a Neural Network AutoencoderCode0
Deep Deterministic Independent Component Analysis for Hyperspectral UnmixingCode0
Improved Deep Spectral Convolution Network For Hyperspectral Unmixing With Multinomial Mixture Kernel and Endmember UncertaintyCode0
Dynamical Hyperspectral Unmixing with Variational Recurrent Neural NetworksCode0
Hyperspectral Blind Unmixing using a Double Deep Image PriorCode0
EndNet: Sparse AutoEncoder Network for Endmember Extraction and Hyperspectral UnmixingCode0
Block-Simultaneous Direction Method of Multipliers: A proximal primal-dual splitting algorithm for nonconvex problems with multiple constraintsCode0
A Gaussian mixture model representation of endmember variability in hyperspectral unmixingCode0
Deep Spectral Convolution Network for HyperSpectral UnmixingCode0
Dual Simplex Volume Maximization for Simplex-Structured Matrix FactorizationCode0
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