Hyperspectral Unmixing

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Most implemented papers archive 2025-07-28

30 shown of 30 papers with code (113 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Block-Simultaneous Direction Method of Multipliers: A proximal primal-dual splitting algorithm for nonconvex problems with multiple constraints
  30 Aug 2017 3 repositories listed
  We introduce a generalization of the linearized Alternating Direction Method of Multipliers to optimize a real-valued function f of multiple arguments with potentially multiple constraints g_∘ on each of them.
• MultiHU-TD: Multifeature Hyperspectral Unmixing Based on Tensor Decomposition
  5 Oct 2023 2 repositories listed
  Matrix models become insufficient when the hyperspectral image (HSI) is represented as a high-order tensor with additional features in a multimodal, multifeature framework.
• UnMix-NeRF: Spectral Unmixing Meets Neural Radiance Fields
  27 Jun 2025 1 repository listed
  Neural Radiance Field (NeRF)-based segmentation methods focus on object semantics and rely solely on RGB data, lacking intrinsic material properties.
• Temperature scaling unmixing framework based on convolutional autoencoder
  29 Apr 2024 1 repository listed
  In addition, a CAE network is designed under the TSU framework in this paper, called TSUCAE.
• Semi-NMF Regularization-Based Autoencoder Training for Hyperspectral Unmixing
  5 Apr 2024 1 repository listed
  Hyperspectral Unmixing (HSU) refers to the procedure of decomposing measured pixel spectra into a set of constituent spectral signatures known as endmembers and a corresponding set of fractional mixing ratios.
• Dual Simplex Volume Maximization for Simplex-Structured Matrix Factorization
  29 Mar 2024 1 repository listed
  Simplex-structured matrix factorization (SSMF) is a generalization of nonnegative matrix factorization, a fundamental interpretable data analysis model, and has applications in hyperspectral unmixing and topic modeling.
• Multi-Scale Convolutional Mask Network for Hyperspectral Unmixing
  10 Jan 2024 1 repository listed
  As an unmixing baseline network, the autoencoder (AE) framework performs well in HU by automatically learning low-dimensional embeddings and reconstructing data.
• Learning Interpretable Deep Disentangled Neural Networks for Hyperspectral Unmixing
  3 Oct 2023 1 repository listed
  The model is learned end-to-end using stochastic backpropagation, and trained using a self-supervised strategy which leverages benefits from semi-supervised learning techniques.
• Hyperspectral Blind Unmixing using a Double Deep Image Prior
  21 Aug 2023 1 repository listed
  With the rise of machine learning, hyperspectral image (HSI) unmixing problems have been tackled using learning-based methods.
• Image Processing and Machine Learning for Hyperspectral Unmixing: An Overview and the HySUPP Python Package
  18 Aug 2023 1 repository listed
  Additionally, we draw a critical comparison between advanced and conventional techniques from the three categories.
• Dynamical Hyperspectral Unmixing with Variational Recurrent Neural Networks
  19 Mar 2023 1 repository listed
  First, a stochastic model is proposed to represent both the dynamical evolution of the endmembers and their abundances, as well as the mixing process.
• Towards Robust Hyperspectral Unmixing: Mixed Noise Modeling and Image-Domain Regularization
  16 Feb 2023 1 repository listed
  Second, existing methods do not explicitly account for the effects of stripe noise, which is common in HS measurements, in their formulations, resulting in significant degradation of unmixing performance when such noise…
• Entropic Descent Archetypal Analysis for Blind Hyperspectral Unmixing
  22 Sep 2022 1 repository listed
  In this paper, we introduce a new algorithm based on archetypal analysis for blind hyperspectral unmixing, assuming linear mixing of endmembers.
• Integration of Physics-Based and Data-Driven Models for Hyperspectral Image Unmixing
  11 Jun 2022 1 repository listed
  Spectral unmixing is one of the most important quantitative analysis tasks in hyperspectral data processing.
• Deep Hyperspectral Unmixing using Transformer Network
  31 Mar 2022 1 repository listed
  In this article, we harness the power of transformers to conquer the task of hyperspectral unmixing and propose a novel deep unmixing model with transformers.
• Deep Deterministic Independent Component Analysis for Hyperspectral Unmixing
  7 Feb 2022 1 repository listed
  We develop a new neural network based independent component analysis (ICA) method by directly minimizing the dependence amongst all extracted components.
• Smoothed Separable Nonnegative Matrix Factorization
  11 Oct 2021 1 repository listed
  More recently, Bhattacharyya and Kannan (ACM-SIAM Symposium on Discrete Algorithms, 2020) proposed an algorithm for learning a latent simplex (ALLS) that relies on the assumption that there is more than one nearby data…
• Endmember-Guided Unmixing Network (EGU-Net): A General Deep Learning Framework for Self-Supervised Hyperspectral Unmixing
  21 May 2021 1 repository listed
  Over the past decades, enormous efforts have been made to improve the performance of linear or nonlinear mixing models for hyperspectral unmixing, yet their ability to simultaneously generalize various spectral…
• A Plug-and-Play Priors Framework for Hyperspectral Unmixing
  24 Dec 2020 1 repository listed
  Spectral unmixing is a widely used technique in hyperspectral image processing and analysis.
• Differentiable Programming for Hyperspectral Unmixing using a Physics-based Dispersion Model
  12 Jul 2020 1 repository listed
  The dispersion model is introduced to simulate realistic spectral variation, and an efficient method to fit the parameters is presented.
• Hyperspectral Image Super-resolution via Deep Progressive Zero-centric Residual Learning
  18 Jun 2020 1 repository listed
  Specifically, PZRes-Net learns a high resolution and \textit{zero-centric} residual image, which contains high-frequency spatial details of the scene across all spectral bands, from both inputs in a progressive fashion…
• Regularization Parameter Selection in Minimum Volume Hyperspectral Unmixing
  14 Aug 2019 1 repository listed
  These observations are systematically formulated to find the transition point that, in turn, yields a good parameter.
• Low-Rank Tensor Modeling for Hyperspectral Unmixing Accounting for Spectral Variability
  2 Nov 2018 1 repository listed
  Recently, tensor-based strategies considered low-rank decompositions of hyperspectral images as an alternative to impose low-dimensional structures on the solutions of standard and multitemporal unmixing problems.
• Improved Deep Spectral Convolution Network For Hyperspectral Unmixing With Multinomial Mixture Kernel and Endmember Uncertainty
  3 Aug 2018 1 repository listed
  The results validate that the proposed method obtains state-of-the-art hyperspectral unmixing performance particularly on the real datasets compared to the baseline techniques.
• Deep Spectral Convolution Network for HyperSpectral Unmixing
  22 Jun 2018 1 repository listed
  In this paper, we propose a novel hyperspectral unmixing technique based on deep spectral convolution networks (DSCN).
• Hyperspectral Unmixing Using a Neural Network Autoencoder
  22 Mar 2018 1 repository listed
  Also, deep encoders are tested using different activation functions.
• A Gaussian mixture model representation of endmember variability in hyperspectral unmixing
  29 Sep 2017 1 repository listed
  We show, given the GMM starting premise, that the distribution of the mixed pixel (under the linear mixing model) is also a GMM (and this is shown from two perspectives).
• EndNet: Sparse AutoEncoder Network for Endmember Extraction and Hyperspectral Unmixing
  6 Aug 2017 1 repository listed
  Data acquired from multi-channel sensors is a highly valuable asset to interpret the environment for a variety of remote sensing applications.
• Spectral Unmixing of Hyperspectral Imagery using Multilayer NMF
  12 Aug 2014 1 repository listed
  In this letter we proposed using multilayer NMF (MLNMF) for the purpose of hyperspectral unmixing.
• Nonlinear hyperspectral unmixing with robust nonnegative matrix factorization
  22 Jan 2014 1 repository listed
  This paper introduces a robust mixing model to describe hyperspectral data resulting from the mixture of several pure spectral signatures.