Results 11 to 20 of about 1,407 (163)

A Label-Free Hyperspectral Imaging Device for Ex Vivo Characterization and Grading of Meningioma Tissues. [PDF]

J Biophotonics
HyperProbe1.1 enables rapid, label‐free biochemical mapping of freshly resected meningiomas. By quantifying endogenous biomarkers such as cytochrome c oxidase, hemoglobin derivatives, and lipids, the system reveals molecular signatures consistent with tumor grading and generates spatial maps that visualize metabolic and vascular heterogeneity across ...
Ricci P, Bonaudo C, Ezhov I, Toaha A, Nardini D, Camelia M, Lucidi F, Nozzoli F, Mach T, Tachtsidis I, Rueckert D, Della Puppa A, Giannoni L, Pavone FS.   +13 more
europepmc   +2 more sources

SIP-SRS Imaging of Cell Wall Synthesis Identifies a Synergy between Micafungin and Amphotericin B. [PDF]

Adv Sci (Weinh)
We employed glucose‐d7–based stable isotope probe‐assisted SRS microscopy (SIP‐SRS) C–D imaging to visualize fungal cell wall synthesis and remodeling under antifungal treatment. Amphotericin B (AmB) induced notable daughter cell wall thickening, prompting a combinational therapy with AmB and micafungin.
Zhang M, Zhan Y, Lin H, Chen J, Seleem MN, Mansour M, Cheng JX.   +6 more
europepmc   +2 more sources

A Novel Collaborative Representation Algorithm for Spectral Unmixing of Hyperspectral Remotely Sensed Imagery

IEEE Access, 2021
Hyperspectral unmixing has attracted considerable attentions in recent years and some promising algorithms have been developed. In this paper, collaborative representation–based unmixing (CRU) for hyperspectral images is proposed.
Jing Wang
doaj   +1 more source

A New Deep Convolutional Network for Effective Hyperspectral Unmixing

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Hyperspectral unmixing extracts pure spectral constituents (endmembers) and their corresponding abundance fractions from remotely sensed scenes. Most traditional hyperspectral unmixing methods require the results of other endmember extraction algorithms ...
Xuanwen Tao, Mercedes E. Paoletti, Lirong Han, Zhaoyue Wu, Peng Ren, Javier Plaza, Antonio Plaza, Juan M. Haut   +7 more
doaj   +1 more source

How Hyperspectral Image Unmixing and Denoising Can Boost Each Other

Remote Sensing, 2020
Hyperspectral linear unmixing and denoising are highly related hyperspectral image (HSI) analysis tasks. In particular, with the assumption of Gaussian noise, the linear model assumed for the HSI in the case of low-rank denoising is often the same as the
Behnood Rasti, Bikram Koirala, Paul Scheunders, Pedram Ghamisi   +3 more
doaj   +1 more source

Maximum Likelihood Estimation Based Nonnegative Matrix Factorization for Hyperspectral Unmixing

Remote Sensing, 2021
Hyperspectral unmixing (HU) is a research hotspot of hyperspectral remote sensing technology. As a classical HU method, the nonnegative matrix factorization (NMF) unmixing method can decompose an observed hyperspectral data matrix into the product of two
Qin Jiang, Yifei Dong, Jiangtao Peng, Mei Yan, Yi Sun   +4 more
doaj   +1 more source

ASSESSING AND COMPARING THE PERFORMANCE OF ENDMEMBER EXTRACTION METHODS IN MULTIPLE CHANGE DETECTION USING HYPERSPECTRAL DATA [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019
Endmember extraction is a process to identify the hidden pure source signals from the mixture. Endmember finding has become increasingly important in hyperspectral data exploitation because endmembers can be used to specify unknown particular spectral ...
H. Jafarzadeh, M. Hasanlou
doaj   +1 more source

Superpixel-Based Weighted Collaborative Sparse Regression and Reweighted Low-Rank Representation for Hyperspectral Image Unmixing

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Sparse unmixing with a semisupervised fashion has been applied to hyperspectral remote sensing imagery. However, the imprecise spatial contextual information, the lack of global feature and the high mutual coherences of a spectral library greatly limit ...
Hongjun Su, Cailing Jia, Pan Zheng, Qian Du   +3 more
doaj   +1 more source

On Hyperspectral Unmixing

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021
to appear in IGARSS 2021, Special Session on "The Contributions of Jos\'e Manuel Bioucas-Dias to Remote Sensing Data Processing"
openaire   +2 more sources

Benchmark for Hyperspectral Unmixing Algorithm Evaluation

Informatica, 2023
Over the past decades, many methods have been proposed to solve the linear or nonlinear mixing of spectra inside the hyperspectral data. Due to a relatively low spatial resolution of hyperspectral imaging, each image pixel may contain spectra from multiple materials. In turn, hyperspectral unmixing is finding these materials and their abundances. A few
Vytautas Paura, Virginijus Marcinkevičius   +1 more
openaire   +2 more sources