Results 41 to 50 of about 75,553 (263)

Plugin procedure in segmentation and application to hyperspectral image segmentation

, 2010
In this article we give our contribution to the problem of segmentation with plug-in procedures. We give general sufficient conditions under which plug in procedure are efficient. We also give an algorithm that satisfy these conditions.
Girard, R.
core   +3 more sources

High-resolution cathodoluminescence hyperspectral imaging of nitride nanostructures [PDF]

, 2012
Hyperspectral cathodoluminescence imaging provides spectrally and spatially resolved information on luminescent materials within a single dataset. Pushing the technique toward its ultimate nanoscale spatial limit, while at the same time spectrally ...
Chaowang Liu, Duncan Allsopp, Jochen Bruckbauer, Lethy Krishnan Jagadamma, Norman, Paul R. Edwards, Philip Shields, Press, Robert W. Martin, Tao Wang   +9 more
core   +1 more source

Hyperspectral Neural Radiance Field Method Based on Reference Spectrum

IEEE Access
The Neural Radiance Field (NeRF) method for datasets is gaining attention for its wide applications and research value. Hyperspectral images have also gained many applications in recent years.
Runchuan Ma, Sailing He
doaj   +1 more source

Correntropy Maximization via ADMM - Application to Robust Hyperspectral Unmixing

, 2016
In hyperspectral images, some spectral bands suffer from low signal-to-noise ratio due to noisy acquisition and atmospheric effects, thus requiring robust techniques for the unmixing problem.
Chen, Badong, Halimi, Abderrahim, Honeine, Paul, Zheng, Nanning, Zhu, Fei   +4 more
core   +2 more sources

A low-cost hyperspectral scanner for natural imaging and the study of animal colour vision above and under water [PDF]

, 2019
Hyperspectral imaging is a widely used technology for industrial and scientific purposes, but the high cost and large size of commercial setups have made them impractical for most basic research.
Baden, T, Nevala, N E
core   +1 more source

Hyperspectral Imaging

Hyperspectral imaging (HSI) is an advanced sensing modality that simultaneously captures spatial and spectral information, enabling non-invasive, label-free analysis of material, chemical, and biological properties. This Primer presents a comprehensive overview of HSI, from the underlying physical principles and sensor architectures to key steps in ...
Princess Tiffany D. Mendoza, Paul R. Armstrong, Kaliramesh Siliveru   +2 more
  +5 more sources

Novel View Synthesis and Dataset Augmentation for Hyperspectral Data Using NeRF

IEEE Access
Hyperspectral data for the 3D domain is relatively difficult to acquire. Existing hyperspectral datasets are unsuitable for 3D research, suffer from issues of severe data scarcity, and a lack of multi-perspective images of the same object, etc.
Runchuan Ma, Tengfei Ma, Deyu Guo, Sailing He   +3 more
doaj   +1 more source

Deep Learning in Hyperspectral Image Reconstruction from Single RGB images—A Case Study on Tomato Quality Parameters

Remote Sensing, 2020
Hyperspectral imaging has many applications. However, the high device costs and low hyperspectral image resolution are major obstacles limiting its wider application in agriculture and other fields.
Jiangsan Zhao, Dmitry Kechasov, Boris Rewald, Gernot Bodner, Michel Verheul, Nicholas Clarke, Jihong Liu Clarke   +6 more
doaj   +1 more source

Correlation Hyperspectral Imaging

Physical Review Letters
Hyperspectral imaging aims at providing information on both the spatial and the spectral distribution of light, with high resolution. However, state-of-the-art protocols are characterized by an intrinsic trade-off imposing to sacrifice either resolution or image acquisition speed.
Gianlorenzo Massaro, Francesco V. Pepe, Milena D’Angelo   +2 more
openaire   +4 more sources

Unmixing of Hyperspectral Data Using Robust Statistics-based NMF

, 2012
Mixed pixels are presented in hyperspectral images due to low spatial resolution of hyperspectral sensors. Spectral unmixing decomposes mixed pixels spectra into endmembers spectra and abundance fractions.
Ghassemian, Hassan, Rajabi, Roozbeh
core   +1 more source