Results 61 to 70 of about 9,466 (207)
Bioanalytical TERS and Advanced Data Processing Methods
Journal of Raman Spectroscopy, EarlyView.Tip‐enhanced Raman spectroscopy delivers label‐free, subnanometer vibrational imaging of biological systems. Recent advances in instrumentation, data analysis, and ambient/liquid operation enable surface‐selective mapping of molecular heterogeneity in proteins, nucleic acids, membranes, and viruses, positioning TERS as a powerful platform for nanoscale
Sarika Joshi +6 more
wiley +1 more source
Self-Dictionary Sparse Regression for Hyperspectral Unmixing: Greedy Pursuit and Pure Pixel Search are Related [PDF]
, 2015 This paper considers a recently emerged hyperspectral unmixing formulation based on sparse regression of a self-dictionary multiple measurement vector (SD-MMV) model, wherein the measured hyperspectral pixels are used as the dictionary.
Bioucas-Dias, José M. +3 more
core +2 more sources
Limnology and Oceanography: Methods, EarlyView.Abstract Cyanobacterial and other algal blooms are an environmental concern in waterbodies worldwide. While these blooms are a nuisance for recreational activities, they can also be harmful to human and wildlife health when the algae produce and release toxins.
Natalie C. Hall +7 more
wiley +1 more source
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Sparse unmixing methods have been extensively studied as a popular topic in hyperspectral image analysis for several years. Fundamental model-based unmixing problems can be better reformulated by exploiting sparse constraints in different forms. Gradient-
Yapeng Miao, Bin Yang
doaj +1 more source
Robust Linear Spectral Unmixing using Anomaly Detection
, 2015 This paper presents a Bayesian algorithm for linear spectral unmixing of hyperspectral images that accounts for anomalies present in the data. The model proposed assumes that the pixel reflectances are linear mixtures of unknown endmembers, corrupted by ...
Altmann, Yoann +2 more
core +1 more source
Gradients in urban material composition: A new concept to map cities with spaceborne imaging spectroscopy data [PDF]
, 2019 To understand processes in urban environments, such as urban energy fluxes or surface temperature patterns, it is important to map urban surface materials. Airborne imaging spectroscopy data have been successfully used to identify urban surface materials
Feilhauer, Hannes +3 more
core +2 more sources
VIEW, EarlyView.In this work, we develop submicron‐resolution mapping of intracellular lipid elements (SMILE) as an extraction‐free vibrational spectroscopic imaging platform based on hyperspectral stimulated Raman scattering microscopy with a spectral analysis pipeline for pixel‐resolved lipid profiling.
Yihui Zhou +10 more
wiley +1 more source
Cluster-Wise Weighted NMF for Hyperspectral Images Unmixing with Imbalanced Data
Remote Sensing, 2021 Hyperspectral unmixing is an important technique for analyzing remote sensing images which aims to obtain a collection of endmembers and their corresponding abundances.
Xiaochen Lv, Wenhong Wang, Hongfu Liu
doaj +1 more source
Bi-Objective Nonnegative Matrix Factorization: Linear Versus Kernel-Based Models
, 2015 Nonnegative matrix factorization (NMF) is a powerful class of feature extraction techniques that has been successfully applied in many fields, namely in signal and image processing.
Honeine, Paul, Zhu, Fei
core +3 more sources
Spatial and temporal scales in plant phenotyping for crop water stress assessment: A review
The Plant Phenome Journal, Volume 9, Issue 1, December 2026.Abstract Water stress is a major limiting factor for crop productivity worldwide, and its impacts are intensifying due to climate variability and increasing water scarcity. This review focuses on the spatial and temporal scales in plant phenotyping as a critical approach to improving crop water‐stress assessment and supporting precision water ...
Daniel Kingsley Cudjoe +3 more
wiley +1 more source