Results 61 to 70 of about 919,951 (170)
SNMF-Net: Learning a Deep Alternating Neural Network for Hyperspectral Unmixing [PDF]
, 2021 Hyperspectral unmixing is recognized as an important tool to learn the constituent materials and corresponding distribution in a scene. The physical spectral mixture model is always important to tackle this problem because of its highly ill-posed nature.
Xiong, F +9 more
core +1 more source
PhotonicsHyperspectral unmixing (HU) requires effective modeling of spectral–spatial information and local–global feature interactions to achieve accurate abundance estimation and endmember extraction.
Xinyu Cui +3 more
doaj +1 more source
Hyperspectral Image Resolution Enhancement Based on Spectral Unmixing and Information Fusion [PDF]
, 2011 Hyperspectral imaging sensors exibit high spectral resolution, but normally low spatial resolution. This leads to spectral signatures of pixels originating from different object types. Such pixels are called mixed pixels.
Avbelj, Janja +4 more
core
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
core +1 more source
Remote Sensing for Monitoring and Managing Urban Soils in Coastal Areas: A Review
Soil Use and Management, Volume 42, Issue 3, July‐September 2026.ABSTRACT Coastal urban soils (CUS) exhibit distinct physical–chemical properties due to the combined effects of intense interaction among anthropogenic and natural pressures, resulting in a unique, complex and highly vulnerable system. While CUS are vital for the urban coastal environment and its inhabitants, numerous factors significantly threaten ...
Antonio Ganga +3 more
wiley +1 more source
Bayesian separation of spectral sources under non-negativity and full additivity constraints [PDF]
, 2009 This paper studied Bayesian algorithms for separating linear mixtures of spectral sources under non-negativity and full additivity constraints. These two constraints are required in some applications such as hyperspectral imaging and spectroscopy to get ...
Moussaoui, Saïd +3 more
core +1 more source
Deep Half-Siamese Networks for Hyperspectral Unmixing
, 2021 International audienceOver the past decades, numerous methods have been proposed to solve the linear or nonlinear mixing problems in hyperspectral unmixing (HU).
Hong, Danfeng +4 more
core +1 more source
A Review of Hyperspectral Unmixing Considering Spectral Variability
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingHyperspectral unmixing (HU) is a fundamental task in the analysis and interpretation of hyperspectral images. A large number of HU methods have been developed rapidly, and several review papers have summarized these developments.
Jianing Huang +6 more
doaj +1 more source
Spectral-spatial adversarial network for nonlinear hyperspectral unmixing of imbalanced datasets
International Journal of Applied Earth Observations and Geoinformation, 2023 With its successful application in various fields, hyperspectral unmixing (HU) technology has received extensive attention in remote sensing processing. Recently, various autoencoders based on the linear mixing model (LMM) have been proposed to provide a
Xu Yang, Jianguo Chen, Zihao Chen
doaj +1 more source
Hyperspectral Imaging: The Intelligent Eye to Uncover the Password of Plant Science
Modern Agriculture, Volume 3, Issue 2, December 2025.Hyperspectral imaging (HSI) has emerged as a powerful non‐destructive technique for characterisation of the plant phenotype and physiological traits. The ongoing development of cost‐effective hardware, coupled with standardised acquisition protocols and open‐access spectral libraries, is accelerating its integration with multi‐omics approaches to ...
Jingyan Song +17 more
wiley +1 more source