Results 81 to 90 of about 871,644 (244)
Research on the Hyperspectral-based Unmixing Model of Composite Pigments on Mural Surfaces [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information SciencesMurals constitute an invaluable component of cultural heritage, encapsulating profound artistic and historical significance. Hyperspectral remote sensing, as a non-destructive testing technique, offers an effective means for analysing and identifying ...
Y. Zhang +8 more
doaj +1 more source
Phasor-Based Spatio-Spectral Segmentation for Hyperspectral Fluorescence Microscopy. [PDF]
J BiophotonicsSpatially‐corrected density peak clustering (SC‐DPC) enables high‐accuracy segmentation of hyperspectral fluorescence microscopy data in the presence of significant spectral and spatial overlap between fluorophores. Validated on retinal imaging, SC‐DPC effectively separates overlapping fluorophore spectra in photon‐starved conditions, offering superior
Barna M +4 more
europepmc +2 more sources
Advanced Science, EarlyView.SLC8A1 deficiency in colorectal cancer cells increases intracellular calcium signaling, promoting the secretion of ANXA2‐enriched small extracellular vesicles. These vesicles reprogram tumor‐associated macrophages towards an M2 phenotype, which in turn fosters a tumor microenvironment conducive to radioresistance and is associated with poor patient ...
Yimin Fang +18 more
wiley +1 more source
Graph-Based Adaptive Network With Spatial-Spectral Features for Hyperspectral Unmixing
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingHyperspectral unmixing aims to extract basic material (endmember) spectra and estimate their corresponding fractions (abundances) from observed pixels in hyperspectral images (HSIs).
Hua Dong +4 more
doaj +1 more source
Serial Molecular‐Microstructural Multimodal Intravascular Imaging of Atherosclerotic Plaques in Mice
Advanced Science, EarlyView.A novel longitudinal molecular and microstructural intravascular imaging approach is developed to study murine atherosclerosis. The technique combines a unique surgical model with a miniaturized multimodal device to detect macrophage activity and lipid simultaneously.
Jiawen Li +12 more
wiley +1 more source
Remote Sensing, 2019 Limited to the low spatial resolution of the hyperspectral imaging sensor, mixed pixels are inevitable in hyperspectral images. Therefore, to obtain the endmembers and corresponding fractions in mixed pixels, hyperspectral unmixing becomes a hot spot in ...
Yang Shao, Jinhui Lan
doaj +1 more source
Advanced Intelligent Discovery, EarlyView.Sequential multicolor fluorescence imaging in dynamic microsystems is constrained by acquisition speed and excitation dose. This study introduces a real‐time framework to reconstruct spectrally separated channels from reduced cross‐channel acquisitions (frames containing mixed spectral contributions).
Juan J. Huaroto +3 more
wiley +1 more source
Mixed Fluids of Water and Carbon Dioxide
Geophysical Monograph Series, Page 237-243., 2020 This book is Open Access. A digital copy can be downloaded for free from Wiley Online Library.
Explores the behavior of carbon in minerals, melts, and fluids under extreme conditions
Carbon trapped in diamonds and carbonate-bearing rocks in subduction zones are examples of the continuing exchange of substantial carbon ...
Evan Abramson
wiley +1 more source
Remote Sensing, 2019 Spatial regularized sparse unmixing has been proved as an effective spectral unmixing technique, combining spatial information and standard spectral signatures known in advance into the traditional spectral unmixing model in the form of sparse regression.
Ruyi Feng, Lizhe Wang, Yanfei Zhong
doaj +1 more source
Variability of the endmembers in spectral unmixing: Recent advances [PDF]
2016 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2016 Endmember variability has been identified as one of the main limitations of the usual Linear Mixing Model, conventionally used to perform spectral unmixing of hyperspectral data. The topic is currently receiving a lot of attention from the community, and many new algorithms have recently been developed to model this variability and take it into account.
Drumetz, Lucas +2 more
openaire +3 more sources