Results 21 to 30 of about 19,235 (216)

A blind spectral unmixing in wavelet domain [PDF]

open access: yesIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
Hyperspectral data - Systems, Processing, Information ...
Vijayashekhar S S, Jignesh S. Bhatt
openaire   +3 more sources

Recent advances in photoacoustic blind source spectral unmixing approaches and the enhanced detection of endogenous tissue chromophores

open access: yesFrontiers in Signal Processing, 2022
Recently, the development of learning-based algorithms has shown a crucial role to extract features of vital importance from multi-spectral photoacoustic imaging.
Valeria Grasso   +6 more
doaj   +1 more source

An Improved Hyperspectral Unmixing Approach Based on a Spatial–Spectral Adaptive Nonlinear Unmixing Network

open access: yesIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023
The autoencoder (AE) framework is usually adopted as a baseline network for hyperspectral unmixing. Totally an AE performs well in hyperspectral unmixing through automatically learning low-dimensional embedding and reconstructing data.
Xiao Chen   +5 more
doaj   +1 more source

Spectral Unmixing of Pigments on Surface of Painted Artefacts Considering Spectral Variability [PDF]

open access: yesISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Painted artefacts, such as murals and paintings, are the treasures of human civilization. Pigment is an important component of their surfaces. It is crucial to study the composition and proportion of pigments on the surface of painted artefacts for the ...
Y. Wang   +10 more
doaj   +1 more source

Hyperspectral Sparse Unmixing With Spectral-Spatial Low-Rank Constraint

open access: yesIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
Spectral unmixing is a consequential preprocessing task in hyperspectral image interpretation. With the help of large spectral libraries, unmixing is equivalent to finding the optimal subset of the library entries that can best model the image.
Fan Li   +5 more
doaj   +1 more source

Nonlinear unmixing of minerals based on the log and continuum removal model

open access: yesEuropean Journal of Remote Sensing, 2019
Spectral mixing models for minerals can be complex, and choosing the right unmixing model is indispensable to ensure the accuracy of spectral unmixing. Continuum removal (CR) and natural log operation have the potential to eliminate nonlinear effects in ...
Hengqian Zhao, Xuesheng Zhao
doaj   +1 more source

An Automatic Unmixing Approach to Detect Tissue Chromophores from Multispectral Photoacoustic Imaging

open access: yesSensors, 2020
Multispectral photoacoustic imaging has been widely explored as an emerging tool to visualize and quantify tissue chromophores noninvasively. This modality can capture the spectral absorption signature of prominent tissue chromophores, such as oxygenated,
Valeria Grasso   +2 more
doaj   +1 more source

UNMIX-ME: spectral and lifetime fluorescence unmixing via deep learning

open access: yesBiomedical Optics Express, 2020
Hyperspectral fluorescence lifetime imaging allows for the simultaneous acquisition of spectrally resolved temporal fluorescence emission decays. In turn, the acquired rich multidimensional data set enables simultaneous imaging of multiple fluorescent species for a comprehensive molecular assessment of biotissues.
Jason T. Smith   +2 more
openaire   +2 more sources

Supervised nonlinear spectral unmixing using a post-nonlinear mixing model for hyperspectral imagery [PDF]

open access: yes, 2011
This paper presents a nonlinear mixing model for hyperspectral image unmixing. The proposed model assumes that the pixel reflectances are nonlinear functions of pure spectral components contaminated by an additive white Gaussian noise.
Abderrahim Halimi   +6 more
core   +9 more sources

Joint Bayesian endmember extraction and linear unmixing for hyperspectral imagery [PDF]

open access: yes, 2009
This paper studies a fully Bayesian algorithm for endmember extraction and abundance estimation for hyperspectral imagery. Each pixel of the hyperspectral image is decomposed as a linear combination of pure endmember spectra following the linear mixing ...
Alfred O. Hero   +5 more
core   +9 more sources

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