Results 111 to 120 of about 77,969 (223)

Deep NMF and Autoencoder: A Comparative Analysis for Hyperspectral Unmixing Using Prisma Real Images

In hyperspectral data, mixed pixels are frequent due to the low-medium spatial resolution of the imaging spectrometer, or to intimate mixing effects. Hence the process of blind hyperspectral unmixing, which separates the pixel spectra into a collection ...
Nicoletta Del Buono, Gaetano Settembre, Nicolò Taggio, Flavia Esposito   +3 more
core   +1 more source

Dual graph regularized NMF for hyperspectral unmixing

, 2014
Hyperspectral unmixing is an important technique for estimating fraction of different land cover types from remote sensing imagery. In recent years, nonnegative matrix factorization (NMF) with various constraints have been introduced into hyperspectral ...
Lei Tong, Gao, Y, Jun Zhou, Zhou, Jun, Tong, L, Zhou, J, Tong, Lei, Bai, Xiao, Yongsheng Gao, Bai, X, Xiao Bai, Gao, Yongsheng   +11 more
core   +1 more source

Diffusion Model Based Hyperspectral Unmixing Using Spectral Prior Distribution

Hyperspectral unmixing is a crucial task for identifying the constituent materials and their respective distributions in a scene. Utilizing known spectral libraries as prior information, semi-blind unmixing methods (also known as spectral-library-based ...
Qian, Yuntao, Zhou, Jun, Deng, Keli, Nie, Jie   +3 more
core   +1 more source

Double reweighted sparse regression for hyperspectral unmixing

, 2016
Spectral unmixing is an important technology in hyperspectral image applications. Recently, sparse regression is widely used in hyperspectral unmixing. This paper proposes a double reweighted sparse regression method for hyperspectral unmixing.
Heng-Chao Li, Liao, Wenzhi, Aleksandra Pizurica, Wenzhi Liao, Pizurica, Aleksandra, Li, Hengchao, Wang, Rui, Rui Wang   +7 more
core   +1 more source

Blind and endmember guided autoencoder model for unmixing the absorbance spectra of phytoplankton pigments

Scientific Reports
Hyperspectral sensing of phytoplankton, free-living microscopic photosynthetic organisms, offers a comprehensive and scalable method for assessing water quality and monitoring changes in aquatic ecosystems.
Pritish Naik, Ilkka Pölönen, Pauliina Salmi   +2 more
doaj   +1 more source

A Deep Equilibrium Network for Hyperspectral Unmixing

CoRR
Hyperspectral unmixing (HU) is crucial for analyzing hyperspectral imagery, yet achieving accurate unmixing remains challenging. While traditional methods struggle to effectively model complex spectral-spatial features, deep learning approaches often lack physical interpretability.
Chentong Wang, Jincheng Gao, Fei Zhu, Jie Chen   +3 more
openaire   +3 more sources

L1/2 Sparsity Constrained Nonnegative Matrix Factorization for Hyperspectral Unmixing

, 2010
Hyperspectral unmixing is a crucial preprocessing step for material classification and recognition. In the last decade, nonnegative matrix factorization (NMF) and its extensions have been intensively studied to unmix hyperspectral imagery and recover ...
Jia, Sen, Qian, Yuntao, Zhou, Jun, Robles-Kelly, Antonio, Sen Jia, Jun Zhou, Jia, S, Antonio, RK, Yuntao Qian, Zhou, J, Antonio Robles-Kelly, Qian, Y   +11 more
core   +1 more source

Updated Homogeneity Criteria Based Low-Dimensional Representation for Hyperspectral Unmixing

IEEE Access
Superpixel-based approaches have been proposed for hyperspectral unmixing. The basic assumption of this approach is that the superpixel over-segmentation segments the image into small homogeneous areas.
Jiarui Yi, Huiyi Gao
doaj   +1 more source

SCVolFormer: Spectral Consistency–Guided Volumetric Linear Self–Attention Transformer for Hyperspectral Unmixing

Photonics
Hyperspectral unmixing (HU) requires effective modeling of spectral–spatial information and local–global feature interactions to achieve accurate abundance estimation and endmember extraction.
Xinyu Cui, Xinyue Zhang, Da Sun, Aoran Dai   +3 more
doaj   +1 more source

A Global-to-Local Spectral-Spatial Attention-Based Nonlinearity and Scaled Endmember Variability Parametric Learning Network for Unmixing

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Hyperspectral unmixing has attracted increasing attention in remote sensing applications. Unfortunately, significant unmixing residuals often arise from the coupled nonlinear mixing effects and spectral variability (SV), bringing challenges for reliably ...
Yi Zhao, Bin Yang
doaj   +1 more source