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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 26–50 of 113 papers

TitleStatusHype
Multi-Scale Convolutional Mask Network for Hyperspectral UnmixingCode0
Dual Simplex Volume Maximization for Simplex-Structured Matrix FactorizationCode0
Dynamical Hyperspectral Unmixing with Variational Recurrent Neural NetworksCode0
Towards Robust Hyperspectral Unmixing: Mixed Noise Modeling and Image-Domain RegularizationCode0
Spectral Unmixing of Hyperspectral Imagery using Multilayer NMFCode0
Transformer based Endmember Fusion with Spatial Context for Hyperspectral Unmixing—0
Effective Spectral Unmixing via Robust Representation and Learning-based Sparsity—0
A spatial compositional model (SCM) for linear unmixing and endmember uncertainty estimation—0
A General Framework for Group Sparsity in Hyperspectral Unmixing Using Endmember Bundles—0
DTU-Net: A Multi-Scale Dilated Transformer Network for Nonlinear Hyperspectral Unmixing—0
An Elliptic Kernel Unsupervised Autoencoder-Graph Convolutional Network Ensemble Model for Hyperspectral Unmixing—0
Hyperspectral Unmixing of Agricultural Images taken from UAV Using Adapted U-Net Architecture—0
Hyperspectral Unmixing: Ground Truth Labeling, Datasets, Benchmark Performances and Survey—0
Deep Nonlinear Hyperspectral Unmixing Using Multi-task Learning—0
An Augmented Linear Mixing Model to Address Spectral Variability for Hyperspectral Unmixing—0
A Data Dependent Multiscale Model for Hyperspectral Unmixing With Spectral Variability—0
Hyperspectral Unmixing Based on Nonnegative Matrix Factorization: A Comprehensive Review—0
Deep Learning-Based Correction and Unmixing of Hyperspectral Images for Brain Tumor Surgery—0
Hyperspectral Unmixing Based on Clustered Multitask Networks—0
A Multibranch Convolutional Neural Network for Hyperspectral Unmixing—0
Hyperspectral unmixing for Raman spectroscopy via physics-constrained autoencoders—0
Hyperspectral Image Generation with Unmixing Guided Diffusion Model—0
Hyperspectral Unmixing Network Inspired by Unfolding an Optimization Problem—0
Deep Diffusion Models and Unsupervised Hyperspectral Unmixing for Realistic Abundance Map Synthesis—0
HYPERION: Hyperspectral Penetrating-type Ellipsoidal Reconstruction for Terahertz Blind Source Separation—0
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