Results 101 to 110 of about 11,320,128 (203)

Multiscale Hyperspectral Pansharpening Network Based on Dual Pyramid and Transformer

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Hyperspectral pansharpening is to fuse a high spatial resolution panchromatic image (PAN) with a low spatial resolution hyperspectral image (LR-HSI) and generate high resolution hyperspectral image (HR-HSI).
Hengyou Wang, Jie Zhang, Lian-Zhi Huo
doaj   +1 more source

Surgical hyperspectral imaging: a systematic review

Computer Assisted Surgery
Hyperspectral imaging (HSI) is a technique that captures and processes information across a wide spectrum of wavelengths, providing detailed spectral data for each pixel in an image to identify and analyze materials or objects. In the surgical domain, it
Hafsa Moontari Ali, Yiming Xiao, Marta Kersten-Oertel   +2 more
doaj   +1 more source

mHC-HSI: Clustering-Guided Hyper-Connection Mamba for Hyperspectral Image Classification

CoRR
Recently, DeepSeek has invented the manifold-constrained hyper-connection (mHC) approach which has demonstrated significant improvements over the traditional residual connection in deep learning models \cite{xie2026mhc}. Nevertheless, this approach has not been tailor-designed for improving hyperspectral image (HSI) classification.
Yimin Zhu 0002, Zack Dewis, Quinn Ledingham, Saeid Taleghanidoozdoozan, Mabel Heffring, Zhengsen Xu, Motasem Alkayid, Megan Greenwood, Lincoln Linlin Xu   +8 more
openaire   +3 more sources

SRS: 3D Mapping and Hyperspectral Imaging (HSI) v1

We have developed a protocol for utilizing stimulated Raman scattering (SRS) to acquirelabel-free measurements of specific macromolecules. When performing SRS imagingwe can acquire total protein, total lipid, unsaturated lipid, and saturatedlipid concentration from distinct Raman shift wavenumbers.
Jorge Villazon, Zhi Li, Yajuan Li, Hongje Jang, Anthony Fung, Lingyan Shi, Sanjay Jain   +6 more
openaire   +1 more source

Nonlinearity detection in hyperspectral images using a polynomial post-nonlinear mixing model [PDF]

, 2012
This paper studies a nonlinear mixing model for hyperspectral image unmixing and nonlinearity detection. The proposed model assumes that the pixel reflectances are nonlinear functions of pure spectral components contaminated by an additive white Gaussian
Altmann, Yoann, Altmann, Yoann; id_orcid, Dobigeon, Nicolas, Tourneret, Jean-Yves   +3 more
core   +1 more source

Supervised nonlinear spectral unmixing using a post-nonlinear mixing model for hyperspectral imagery [PDF]

, 2011
This paper presents a nonlinear mixing model for hyperspectral image unmixing. The proposed model assumes that the pixel reflectances are nonlinear functions of pure spectral components contaminated by an additive white Gaussian noise.
Altmann, Yoann, Altmann, Yoann; id_orcid, Halimi, Abderrahim; id_orcid, Jean-Yves Tourneret, Halimi, Abderrahim, Yoann Altmann, Abderrahim Halimi, Nicolas Dobigeon, Dobigeon, Nicolas, Tourneret, Jean-Yves   +9 more
core   +1 more source

Development of a new spectral library classifier for airborne hyperspectral images on heterogeneous environments [PDF]

, 2011
The classification of hyperspectral images on heterogeneous environments without prior knowledge about the study area is a challenging task. Finding potential pure spectral signatures or endmembers (EM) of the various surface materials within an image is
Mende, Andre, Heiden, Uta, Buchroithner, Manfred, Hoja, Danielle, Bachmann, Martin   +4 more
core  

Hyperspectral imaging (HSI) for intraoperative tumor cell classification [PDF]

Laryngo-Rhino-Otologie, 2019
R Beck, H Köhler, F Goltz, A Dietz, C Chalopin, I Gockel   +5 more
openaire   +1 more source

HSIMAE: A Unified Masked Autoencoder With Large-Scale Pretraining for Hyperspectral Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
With a spurt of progress in deep learning techniques, convolutional neural network-based and transformer-based methods have yielded impressive performance on the hyperspectral image (HSI) classification tasks.
Yue Wang, Ming Wen, Hailiang Zhang, Jinyu Sun, Qiong Yang, Zhimin Zhang, Hongmei Lu   +6 more
doaj   +1 more source

Hyperspectral Image Super-Resolution via Sparsity Regularization-Based Spatial-Spectral Tensor Subspace Representation

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Hyperspectral image super-resolution (HSI-SR), which enhances the spatial resolution of hyperspectral image (HSI) by fusing a low spatial resolution HSI (LR-HSI) with a high spatial resolution multispectral image (HR-MSI), has gained increasing attention
Yidong Peng, Weisheng Li, Xiaobo Luo, Jiao Du   +3 more
doaj   +1 more source