Results 91 to 100 of about 34,632 (306)

Adaptive Markov random fields for joint unmixing and segmentation of hyperspectral image [PDF]

, 2013
Linear spectral unmixing is a challenging problem in hyperspectral imaging that consists of decomposing an observed pixel into a linear combination of pure spectra (or endmembers) with their corresponding proportions (or abundances). Endmember extraction
Eches, Olivier, Benediktsson, Jon Atli, Dobigeon, Nicolas, Tourneret, Jean-Yves   +3 more
core   +1 more source

Real‐Time Multicolor Fluorescence Microscopy via Cross‐Channel Acquisition and Deep‐Learning‐Based Inference

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, Yuxin Jin, Nicholas Roy, Sarthak Misra   +3 more
wiley   +1 more source

Classification techniques for hyperspectral remote sensing [PDF]

, 2011
This study concerns with classification techniques in high dimensional space such as that of Hyperspectral Imaging (HSI) data sets, with objectives of understanding the strength and weakness of various classifiers and at the same time to study how ...
Kam, Firmin
core  

Nonlinear unmixing of hyperspectral images: Models and algorithms [PDF]

, 2013
When considering the problem of unmixing hyperspectral images, most of the literature in the geoscience and image processing areas relies on the widely used linear mixing model (LMM).
McLaughlin, Stephen; id_orcid, Hero, Alfred O, Jean-yves Tourneret, Cédric Richard, Hero, Alfred O., Dobigeon, Nicolas, McLaughlin, Steve, Bermudez, José Carlos M., Alfred O. Hero, Stephen Mclaughlin, Bermudez, José Carlos Moreira, Nicolas Dobigeon, Richard, Cédric, Tourneret, Jean-Yves, José Carlos M. Bermudez, Bermudez, José Carlos M   +14 more
core   +1 more source

Toward Intelligent Multimodal Holography for Real‐Time Chemical Imaging of Dynamic Ion Separation

Advanced Intelligent Discovery, EarlyView.
Intelligent multimodal holography integrates digital off‐axis holography, spectroscopic imaging, and AI‐driven reconstruction to visualize ion transport and chemical dynamics in real time. In this perspective paper, we outline how this approach enables label‐free, chemically specific monitoring of complex environments and discuss its potential to ...
Giovanna Ricchiuti, Sarah I. Allec, Maxim Ziatdinov, Venkateshkumar Prabhakaran   +3 more
wiley   +1 more source

Hyperspectral image unmixing using a multiresolution sticky HDP [PDF]

, 2012
This paper is concerned with joint Bayesian endmember extraction and linear unmixing of hyperspectral images using a spatial prior on the abundance vectors.We propose a generative model for hyperspectral images in which the abundances are sampled from a ...
Hero, Alfred O., Dobigeon, Nicolas, Hero, Alfred, Mittelman, Roni   +3 more
core   +1 more source

Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning

Advanced Intelligent Discovery, EarlyView.
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang, Yongqing Zhang, Xinyu Deng, Hyeon Jeong Lee, Delong Zhang   +4 more
wiley   +1 more source

Spatially Informed Feature Selection and Machine Learning in Matrix‐Assisted Laser Desorption/Ionization Imaging for Cohort‐Scale Molecular Tissue Phenomics in Glioblastoma

Advanced Intelligent Discovery, EarlyView.
Matrix‐assisted laser desorption/ionization imaging‐based identification of reliable small molecule markers across heterogeneous glioblastoma cohorts is challenging with intensity‐only methods. We present spatially informed feature selection (SIFS), a spatially informed framework that prioritizes molecules consistently colocalizing with histopathology.
Shad A. Mohammed, Denis Abu Sammour, Dirk C. Hoffmann, Philipp Sievers, Tobias Bausbacher, Melissa Hahn, Yasemin Ucal, Iris Mildenberger, Christiane A. Opitz, Stefan Schmidt, Michael Platten, Oliver Wasenmüller, Wolfgang Wick, Andreas von Deimling, Tobias Kessler, Carsten Hopf   +15 more
wiley   +1 more source

Spatial Cell Death and Oxidative Stress Dynamics in Gas Plasma‐Treated Tumor Tissues

Advanced NanoBiomed Research, EarlyView.
Schematic representation of the four experimental models to study tissue penetration and oxidation. Four tissue models were used. Human pancreatic cancer cells were grown on the chorioallantois membrane of chicken embryos and gas plasma‐treated in ovo, murine colorectal tumor tissue was gas plasma‐exposed ex vivo, murine squamous cell carcinoma cells ...
Anke Schmidt, Shahrzad Rokhsary, Linus Hübner, Lea Miebach, Sander Bekeschus   +4 more
wiley   +1 more source

TEBS: Temperature–Emissivity–Driven band selection for thermal infrared hyperspectral image classification with structured State-Space model and gated attention

International Journal of Applied Earth Observations and Geoinformation
Thermal infrared hyperspectral images (TIR-HSIs) provide unique spectral insights that are often unattainable with visible imagery, making them invaluable for applications such as land cover classification and geological mapping.
Enyu Zhao, Nianxin Qu, Yulei Wang, Caixia Gao, Jian Zeng   +4 more
doaj   +1 more source