Results 191 to 200 of about 1,244,965 (221)

Quantification of dual-state 5-ALA-induced PpIX fluorescence: methodology and validation in tissue-mimicking phantoms. [PDF]

Phys Med Biol
Ségaud S, Budd C, Elliot M, Stasiuk GJ, Shapey J, Xie Y, Vercauteren T.   +6 more
europepmc   +1 more source

East Siberian ice wedges recording dust transport variability during the Late Pleistocene. [PDF]

Nat Commun
Kim S, Lee H, Kim J, Lee Y, Choi JH, Lee MJ, Kwon UJ, Iwahana G, Opel T, Meyer H, Wetterich S, Fedorov A, Ahn J.   +12 more
europepmc   +1 more source

Improved mapping of Arctic fractional land cover and land cover change from multi-resolution optical remote sensing.

Remote Sens Environ
Zhu X, Wang JA, Sonnentag O, Myers-Smith IH, Yang D, Orndahl KM, Nill L, Caron-Guay A, Laliberté E, Friedl MA.   +9 more
europepmc   +1 more source

Probabilistic Generative Model for Hyperspectral Unmixing Accounting for Endmember Variability

IEEE Transactions on Geoscience and Remote Sensing, 2022
The complex nature of hyperspectral images makes the analysis of spectral signatures a challenging task in remote sensing. For quantitative analysis, spectral unmixing is a well-established and effective tool to analyze the spectra and spatial ...
Yoann Altmann, Shuaikai Shi, Jie Chen
exaly   +4 more sources

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A Novel Endmember Bundle Extraction and Clustering Approach for Capturing Spectral Variability Within Endmember Classes

IEEE Transactions on Geoscience and Remote Sensing, 2016
Spectral variability, unrelated to the purity of endmembers, can change the geometry of the dataspace and affect conventional methods used to identify endmembers. Several methods have been developed to identify and extract endmember bundles representing the spectral variability within each endmember class.
Arman Melkumyan, Tatsumi Uezato, Anna Chlingaryan   +2 more
exaly   +2 more sources

Variability of the Endmembers in Spectral Unmixing

Data Handling in Science and Technology, 2019
Spectral unmixing is an inverse problem in hyperspectral imaging that aims at recovering the spectra of the pure constituents of an image (called endmembers), as well as at estimating the proportions of said materials in each pixel (called abundances).
Christian Jutten, Lucas Drumetz, Jocelyn Chanussot   +2 more
exaly   +4 more sources

Endmember Variability in Spectral Mixture Analysis: A Review

Remote Sensing of Environment, 2011
The composite nature of remotely sensed spectral information often masks diagnostic spectral features and hampers the detailed identification and mapping of targeted constituents of the earth's surface. Spectral Mixture Analysis (SMA) is a well established and effective technique to address this mixture problem.
Greg Asner, Ben Somers, Pol Coppin
exaly   +2 more sources

Endmember Variability in Hyperspectral Analysis: Addressing Spectral Variability During Spectral Unmixing

IEEE Signal Processing Magazine, 2014
Variable illumination and environmental, atmospheric, and temporal conditions cause the measured spectral signature for a material to vary within hyperspectral imagery. By ignoring these variations, errors are introduced and propagated throughout hyperspectral image analysis.
Alina Zare
exaly   +3 more sources

A Novel Endmember Bundle Extraction Framework for Capturing Endmember Variability by Dynamic Optimization

IEEE Transactions on Geoscience and Remote Sensing
Rong Liu, Xiaoqiong Qin, Linfu Xie
exaly   +2 more sources

Variational Autoencoders for Hyperspectral Unmixing with Endmember Variability

ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021
Spectral signatures are usually affected by variations in environmental conditions. The spectral variability is thus one of the most important and challenging problems to be addressed in hyperspectral unmixing. Generally, it is a non-trivial task to model the endmember variability, and existing spectral unmixing methods that address the spectral ...
Shuaikai Shi, Min Zhao 0014, Lijun Zhang 0004, Jie Chen 0022   +3 more
openaire   +2 more sources