Results 51 to 60 of about 32,344 (307)

Anomaly targets detection of hyperspectral imagery based on wavelet transform and sparse representation

MATEC Web of Conferences, 2018
The research of anomaly target detection algorithm in hyperspectral imagery is a hot issue, which has important research value. In order to overcome low efficiency of current anomaly target detection in hyperspectral image, an anomaly detection algorithm
Baozhi Cheng
doaj   +1 more source

Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches [PDF]

, 2012
Imaging spectrometers measure electromagnetic energy scattered in their instantaneous field view in hundreds or thousands of spectral channels with higher spectral resolution than multispectral cameras.
Paul Gader, Jocelyn Chanussot, Qian Du, Gader, Paul, Antonio Plaza, José M. Bioucas-dias, Chanussot, Jocelyn, Dobigeon, Nicolas, Plaza, Antonio, Du, Qian, Mario Parente, Bioucas-Dias, José M., Nicolas Dobigeon, Parente, Mario   +13 more
core   +1 more source

High Light Utilization and Color Rendering in Vacuum‐Deposited Semitransparent Perovskite Solar Cells

Advanced Materials, EarlyView.
In this work, low bandgap (≈1.55 eV) semitransparent perovskite solar cells (ST‐PSCs) having thin (thickness < ≈100 nm) perovskite layers and transparent conductive oxide‐based rear electrodes are fabricated using vacuum‐deposition methods. Two different ST‐PSCs demonstrated a high light utilization efficiency value of 4.2 (PCE: 9.26% and AVT: 45.3 ...
Abhyuday Paliwal, Manuel Romero, Lennart van den Hengel, Nathan Rodkey, Kassio P. S. Zanoni, Gabriel Lozano, Cristina Roldán‐Carmona, Michele Sessolo, Hernán Míguez, Henk J. Bolink   +9 more
wiley   +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

Rapid Hyperspectral Imaging System via Sub-Sampling Coding

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
In recent years, with the rapid advancement of hyperspectral imaging technology, a growing number of hyperspectral reconstruction approaches have arisen.
Bingchen Wei, Zhuang Zhao, Jing Han, Jun Lu, Haocun Qi   +4 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

Ultra‐Confinement of Polaritons in Single Atomic Layer Ag Photonic Quantum Dots

Advanced Materials, EarlyView.
Strong confinement of surface phonon polaritons of silicon carbide was achieved in photonic quantum dots fabricated from van der Waals heterostructure of epitaxial graphene over single‐atomic layer silver. Scattering‐type scanning near‐field optical microscopy combined with an analytical approach, developed to reveal local propagation constants with ...
Xinyi Li, Tetyana Ignatova, Chengye Dong, Krishnan Mekkanamkulam Ananthanarayanan, Rinu Abraham Maniyara, Arpit Jain, Furkan Turker, Vinay Kammarchedu, Aida Ebrahimi, Joshua A. Robinson, Slava V. Rotkin   +10 more
wiley   +1 more source

Three-Dimensional Spatial-Spectral Filtering Based Feature Extraction for Hyperspectral Image Classification

Advances in Electrical and Computer Engineering, 2017
Hyperspectral pixels which have high spectral resolution are used to predict decomposition of material types on area of obtained image. Due to its multidimensional form, hyperspectral image classification is a challenging task. Hyperspectral images are
AKYUREK, H. A., KOCER, B.
doaj   +1 more source

Delving Into Classifying Hyperspectral Images via Graphical Adversarial Learning

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020
Recent remote sensing literature has seen generative adversarial network (GAN)-based models developed for hyperspectral image classification, especially in a spatiospectral manner.
Guangxing Wang, Peng Ren
doaj   +1 more source

A Deep Learning-Based Hyperspectral Keypoint Representation Method and Its Application for 3D Reconstruction

IEEE Access, 2022
In previous studies, the keypoints and their feature descriptors of a hyperspectral image have not received enough attention. Compared with RGB images, the rich feature information of a hyperspectral image can not only constrain the spatial positions of ...
Tengfei Ma, Yuxin Xing, Dawei Gong, Zijian Lin, Yuanpeng Li, Jiong Jiang, Sailing He   +6 more
doaj   +1 more source