Results 41 to 50 of about 309,259 (214)
Superpixel and low-rank double-sparse regression hyperspectral unmixing
, 2021 These are data and code for the paper "Superpixel and low-rank double-sparse regression hyperspectral ...
Shuaiyang Zang
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Joint-Sparse-Blocks Regression for Total Variation Regularized Hyperspectral Unmixing
IEEE Access, 2019 Sparse unmixing has attracted much attention in recent years. It aims at estimating the fractional abundances of pure spectral signatures in mixed pixels in hyperspectral images.
Jie Huang +3 more
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IVIU-Net: Implicit Variable Iterative Unrolling Network for Hyperspectral Sparse Unmixing
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 At present, an emerging technique called the algorithm unrolling approach has attracted wide attention, because it is capable of developing efficient and interpretable layers to eliminate the black-box nature of deep learning (DL).
Yuantian Shao, Qichao Liu, Liang Xiao
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Nonlinear unmixing of hyperspectral images using a generalized bilinear model [PDF]
, 2011 Nonlinear models have recently shown interesting properties for spectral unmixing. This paper studies a generalized bilinear model and a hierarchical Bayesian algorithm for unmixing hyperspectral images. The proposed model is a generalization not only of
Altmann, Yoann +9 more
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Hyperspectral Unmixing Via Nonconvex Sparse and Low-Rank Constraint
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 In recent years, sparse unmixing has attracted significant attention, as it can effectively avoid the bottleneck problems associated with the absence of pure pixels and the estimation of the number of endmembers in hyperspectral scenes.
Hongwei Han +7 more
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Sparse and Low-Rank Constrained Tensor Factorization for Hyperspectral Image Unmixing
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Third-order tensors have been widely used in hyperspectral remote sensing because of their ability to maintain the 3-D structure of hyperspectral images.
Pan Zheng, Hongjun Su, Qian Du
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Hyperspectral unmixing using weighted sparse regression with total variation regularization
, 2022 Spectral unmixing aims at identifying the pure spectral signatures in hyperspectral images and simultaneously estimating their proportions in each pixel of the scene.
Ma, Zheng +9 more
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Sparse {Spectral} {Unmixing} with {Endmember} {Groups} {Pre}-{Selection}
, 2013 Sparse hyperspectral unmixing is a relatively new method for automatic endmember detection and abundance estimation using large overcomplete dictionaries.
Bieniarz, Jakub;Zhu, Xiao Xiang;Müller, Rupert;Reinartz, Peter
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IEEE Access, 2021 Hyperspectral unmixing has attracted considerable attentions in recent years and some promising algorithms have been developed. In this paper, collaborative representation–based unmixing (CRU) for hyperspectral images is proposed.
Jing Wang
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Double Regression Sparse Unmixing for Hyperspectral Image
, 2020 This file contains MATLAB code and data set, which is about “Double Regression Sparse Unmixing for Hyperspectral ...
Zhang Shuaiyang
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