Results 11 to 20 of about 871,644 (244)
On the use of overcomplete dictionaries for spectral unmixing [PDF]
2012 4th Workshop on Hyperspectral Image and Signal Processing (WHISPERS), 2012 Hyperspectral unmixing is a sub pixel classification method which aims at recovering fraction and type of materials mixed in a single pixel. This work addresses the unmixing problem from the compressive sensing point of view by using overcomplete dictionaries enabling automatization of the process.
Bieniarz, Jakub +3 more
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Spectral Unmixing With Perturbed Endmembers
IEEE Transactions on Geoscience and Remote Sensing, 2017 We consider the problem of supervised spectral unmixing with a fully-perturbed linear mixture model where the given endmembers, as well as the observations of the spectral image, are subject to perturbation due to noise, error, mismatch, etc. We calculate the Fisher information matrix and the Cramer-Rao lower bound associated with the estimation of the
Reza Arablouei
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Probabilistic Mixture Model-Based Spectral Unmixing
Applied SciencesSpectral unmixing attempts to decompose a spectral ensemble into the constituent pure spectral signatures (called endmembers) along with the proportion of each endmember.
Oliver Hoidn +2 more
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SPATIAL INTERPOLATION AS A TOOL FOR SPECTRAL UNMIXING OF REMOTELY SENSED IMAGES [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012 Super resolution-based spectral unmixing (SRSU) is a recently developed method for spectral unmixing of remotely sensed imagery, but it is too complex to implement for common users who are interested in land cover mapping.
L. Xi, C. Xiaoling
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Applied Sciences, 2022 The purpose of hyperspectral unmixing (HU) is to obtain the spectral features of materials (endmembers) and their proportion (abundance) in a hyperspectral image (HSI).
Baohua Jin +4 more
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Spectral Unmixing With Multiple Dictionaries [PDF]
IEEE Geoscience and Remote Sensing Letters, 2018 Spectral unmixing aims at recovering the spectral signatures of materials, called endmembers, mixed in a hyperspectral or multispectral image, along with their abundances. A typical assumption is that the image contains one pure pixel per endmember, in which case spectral unmixing reduces to identifying these pixels.
Jeremy E. Cohen, Nicolas Gillis
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 With the support of spectral libraries, sparse unmixing techniques have gradually developed. However, some existing sparse unmixing algorithms suffer from problems, such as insufficient utilization of spatial information and sensitivity to noise.
Yao Liang +4 more
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USE SATELLITE IMAGES AND IMPROVE THE ACCURACY OF HYPERSPECTRAL IMAGE WITH THE CLASSIFICATION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015 The best technique to extract information from remotely sensed image is classification. The problem of traditional classification methods is that each pixel is assigned to a single class by presuming all pixels within the image.
P. Javadi
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Deep-Learning-Driven High-Fidelity In Vivo Hyperspectral Fluorescence Imaging Under Extreme Photon-Limited Conditions. [PDF]
Adv Sci (Weinh)Highly overlapping fluorescent signals become distinguishable in photon‐limited living organisms via advanced imaging with intelligent reconstruction. The resulting in vivo hyperspectral imaging capability reveals nanoplastic uptake and circulation in live zebrafish, providing a new approach for studying complex biological and environmental processes ...
Li R +11 more
europepmc +2 more sources
Spectral unmixing techniques for optoacoustic imaging of tissue pathophysiology [PDF]
Philosophical Transactions Series A, Mathematical, Physical, and Engineering Sciences, 2017 Stratis Tzoumas, Vasilis Ntziachristos
exaly +2 more sources