Results 31 to 40 of about 2,924,189 (218)
Sensors, 2023 Hyperspectral band selection plays an important role in overcoming the curse of dimensionality. Recently, clustering-based band selection methods have shown promise in the selection of informative and representative bands from hyperspectral images (HSIs).
Zelin Li, Wenhong Wang
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Deep Tensor Attention Prior Network for Hyperspectral Image Denoising
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Hyperspectral imaging techniques can generate continuous narrowband images with a high spectral resolution. However, owing to environmental disturbances, atmospheric effects, and hardware limitations of hyperspectral imaging sensors, captured ...
Weilin Shen +3 more
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Hyperspectral Imaging (HSI) in anatomic left liver resection
International Journal of Surgery Case Reports, 2019 Abstract Introduction Anatomic liver resection is based on the description of functional segments, which rely on the organs arterial and portal venous blood supply. Vascular inflow control of the left liver is performed by occlusion of the left hepatic artery (LHA) and left portal vein (LPV ...
Sucher, Robert +7 more
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Nonlinear spectral unmixing of hyperspectral images using Gaussian processes [PDF]
, 2012 This paper presents an unsupervised algorithm for nonlinear unmixing of hyperspectral images. The proposed model assumes that the pixel reflectances result from a nonlinear function of the abundance vectors associated with the pure spectral components ...
Altmann, Yoann +5 more
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In vivo evaluation of a hyperspectral imaging system for minimally invasive surgery (HSI-MIS)
Surgical Endoscopy, 2023 Abstract Background Hyperspectral Imaging (HSI) is a reliable and safe imaging method for taking intraoperative perfusion measurements. This is the first study translating intraoperative HSI to an in vivo laparoscopic setting using a CE-certified HSI-system for minimally invasive surgery (HSI-MIS).
Madeleine T. Thomaßen +9 more
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Maize disease detection based on spectral recovery from RGB images
Frontiers in Plant Science, 2022 Maize is susceptible to infect pest disease, and early disease detection is key to preventing the reduction of maize yields. The raw data used for plant disease detection are commonly RGB images and hyperspectral images (HSI).
Jun Fu +10 more
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Residual component analysis of hyperspectral images - Application to joint nonlinear unmixing and nonlinearity detection [PDF]
, 2014 This paper presents a nonlinear mixing model for joint hyperspectral image unmixing and nonlinearity detection. The proposed model assumes that the pixel reflectances are linear combinations of known pure spectral components corrupted by an additional ...
Altmann, Yoann +10 more
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Remote Sensing, 2020 3D convolutional neural networks (CNNs) have been demonstrated to be a powerful tool in hyperspectral images (HSIs) classification. However, using the conventional 3D CNNs to extract the spectral−spatial feature for HSIs results in too many ...
Qin Xu, Yong Xiao, Dongyue Wang, Bin Luo
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, 2022 International audienceClustering large hyperspectral images (HSIs) is a very challenging problem because large HSIs have high dimensionality, large spectral variability, and large computational and memory consumption. Recently, sparse subspace clustering
Xiao, Liang +7 more
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Nonlinear unmixing of hyperspectral images using a generalized bilinear model [PDF]
, 2011 Nonlinear models have recently shown interesting properties for spectral unmixing. This paper studies a generalized bilinear model and a hierarchical Bayesian algorithm for unmixing hyperspectral images. The proposed model is a generalization not only of
Altmann, Yoann +9 more
core +1 more source