Spatial validation of spectral unmixing results: A systematic review
RM Cavalli - Remote Sensing, 2023 - mdpi.com
The pixels of remote images often contain more than one distinct material (mixed pixels),
and so their spectra are characterized by a mixture of spectral signals. Since 1971, a shared …
and so their spectra are characterized by a mixture of spectral signals. Since 1971, a shared …
Hyperspectral sparse unmixing based on a novel adaptive total variation regularization
M Ma, C Xu, J Zhang, S Wang, C Deng… - Infrared Physics & …, 2022 - Elsevier
Hyperspectral unmixing realizes the unmixing by determining the pure substances
(endmembers) and their proportion (abundances) in the mixing pixels. Most of the previous …
(endmembers) and their proportion (abundances) in the mixing pixels. Most of the previous …
Piecewise Weighted Smoothing Regularization in Tight Framelet Domain for Hyperspectral Image Restoration
F Ma, S Liu, F Yang, G Xu - IEEE Access, 2023 - ieeexplore.ieee.org
Hyperspectral images captured by remote-sensing satellites are easily corrupted by various
types of noise. Generally, hyperspectral signatures appear to be scattered in spatial-spectral …
types of noise. Generally, hyperspectral signatures appear to be scattered in spatial-spectral …
Spectral weighted sparse unmixing based on adaptive total variation and low-rank constraints
C Xu - Scientific Reports, 2024 - nature.com
Hyperspectral sparse unmixing, an image processing technique, leverages a spectral library
enriched with endmember spectral information as a prerequisite. It decomposes the …
enriched with endmember spectral information as a prerequisite. It decomposes the …
Multiscale reweighted smoothing regularization in curvelet domain for hyperspectral image denoising
F Ma, S Liu, S Huo, F Yang, G Xu - International Journal of Remote …, 2024 - Taylor & Francis
Hyperspectral images are easily contaminated by multi-modal noise in the process of data
acquisition. Generally, hyperspectral signatures and noise appear unexpectedly scattered in …
acquisition. Generally, hyperspectral signatures and noise appear unexpectedly scattered in …
Superpixel linear independent preprocessing for endmember extraction
R Franco, MC Torres-Madronero… - … Journal of Remote …, 2023 - Taylor & Francis
One of the limitations of remote sensing is the low spatial resolution of the open-access
multispectral sensors, generating a mixture of spatial information. The mixed pixels can be …
multispectral sensors, generating a mixture of spatial information. The mixed pixels can be …
Elastic reweighted sparsity regularized sparse unmixing for hyperspectral image analysis
J Wang, Q Zhang, Y Zhang - Digital Signal Processing, 2024 - Elsevier
Sparse unmixing is a crucial component in the analysis of hyperspectral images because of
its ability to sparsely estimate abundances with a spectral library of considerable scale. The …
its ability to sparsely estimate abundances with a spectral library of considerable scale. The …
基于深度图像先验的高光谱图像去噪方法.
马飞， 王梓璇， 刘思雨 - Laser Technology, 2024 - search.ebscohost.com
为了避免现有的高光谱图像去噪优化模型仅考虑有限的高光谱内在结构特点,
并未实现图像特征的精确表征的问题, 采用了一种基于空谱深度图像先验与平滑的高光谱图像去 …
并未实现图像特征的精确表征的问题, 采用了一种基于空谱深度图像先验与平滑的高光谱图像去 …