Results 11 to 20 of about 11,517,403 (217)

Self-Dictionary Regression for Hyperspectral Image Super-Resolution

Remote Sensing, 2018
Due to sensor limitations, hyperspectral images (HSIs) are acquired by hyperspectral sensors with high-spectral-resolution but low-spatial-resolution. It is difficult for sensors to acquire images with high-spatial-resolution and high-spectral-resolution
Dongsheng Gao, Zhentao Hu, Renzhen Ye
doaj   +2 more sources

An Effective Classification Scheme for Hyperspectral Image Based on Superpixel and Discontinuity Preserving Relaxation

Remote Sensing, 2019
Hyperspectral image (HSI) classification is one of the most active topics in remote sensing. However, it is still a nontrivial task to classify the hyperspectral data accurately, since HSI always suffers from a large number of noise pixels, the ...
Fuding Xie, Cunkuan Lei, Jun Yang, Cui Jin   +3 more
doaj   +2 more sources

A Novel Analysis Dictionary Learning Model Based Hyperspectral Image Classification Method

Remote Sensing, 2019
Supervised hyperspectral image (HSI) classification has been acknowledged as one of the fundamental tasks of hyperspectral data analysis. Witnessing the success of analysis dictionary learning (ADL)-based method in recent years, we propose an ADL-based ...
Wei Wei, Mengting Ma, Cong Wang, Lei Zhang, Peng Zhang, Yanning Zhang   +5 more
doaj   +2 more sources

Electrolyzers-HSI: Close-Range Multi-Scene Hyperspectral Imaging Benchmark Dataset

Scientific Data
Electrolyzers-HSI Dataset Description: The Electrolyzers-HSI dataset is a multiscene RGB-Hyperspectral benchmark dataset comprising 55 scene of shredded Electrolyzers samples.
Belahsen, Ymane, Ghamisi, Pedram, Scheunders, Paul, Fuchs, Margret, Gloaguen, Richard, Afifi, Ahmed Jamal, Arbash, Elias, Afifi, Ahmed Jamal Mohammaed   +7 more
core   +7 more sources

Improved Transformer Net for Hyperspectral Image Classification

Remote Sensing, 2021
In recent years, deep learning has been successfully applied to hyperspectral image classification (HSI) problems, with several convolutional neural network (CNN) based models achieving an appealing classification performance.
Yuhao Qing, Wenyi Liu, Liuyan Feng, Wanjia Gao   +3 more
doaj   +2 more sources

Hyperspectral Image Super-Resolution by Deep Spatial-Spectral Exploitation

Remote Sensing, 2019
Limited by the existing imagery sensors, hyperspectral images are characterized by high spectral resolution but low spatial resolution. The super-resolution (SR) technique aiming at enhancing the spatial resolution of the input image is a hot topic in ...
Jing Hu, Minghua Zhao, Yunsong Li
doaj   +2 more sources

An Integrated Framework Coupling Hierarchical Hyperspectral i-trait Screening, Gene Identification, and Functional Validation for Genetic Dissection of Salt Tolerance in Cotton. [PDF]

Adv Sci (Weinh)
An integrated phenomics–genomics framework captures dynamic salt‐stress responses in laboratory‐grown cotton seedlings through time‐series hyperspectral imaging and non‐destructive i‐trait extraction. Hierarchical screening identifies biologically relevant, heritable, and non‐redundant traits for high‐resolution GWAS, identifying GhST7.
Xu B, Liu L, Yu M, Guo Y, Ye J, Zhang J, Zhao R, Yang J, Yang W, Xu Y, Fan L, Yang Z.   +11 more
europepmc   +2 more sources

HSI-MSER: Hyperspectral Image Registration Algorithm Based on MSER and SIFT [PDF]

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
This work was supported in part by Ministerio de Ciencia e Innovación, Government of Spain [grant number PID2019-104834GB-I00], and Consellería de Cultura, Educación e Universidade [grant numbers ED431C 2018/19, and accreditation 2019-2022 ED431G-2019/04]. All are co--funded by the European Regional Development Fund (ERDF).
Álvaro Ordóñez, Álvaro Acción, Francisco Argüello, Dora B. Heras   +3 more
openaire   +5 more sources

Improved sparse representation using adaptive spatial support for effective target detection in hyperspectral imagery [PDF]

, 2013
With increasing applications of hyperspectral imagery (HSI) in agriculture, mineralogy, military, and other fields, one of the fundamental tasks is accurate detection of the target of interest.
Li, Xiaohui, Ren, Jinchang, Marshall, Stephen, Zhao, Chunhui   +3 more
core   +3 more sources

AI-Powered TAT-Net Hyperspectral Imaging for Rapid and Accurate Differentiation of Sinonasal Inverted Papilloma and Malignancy. [PDF]

World J Otorhinolaryngol Head Neck Surg
ABSTRACT Background Sinonasal inverted papilloma (IP) and malignancies share overlapping clinical and endoscopic features, and conventional histopathology frequently requires time‐consuming adjunct immunohistochemistry. Hyperspectral imaging (HSI) can capture subtle spectral changes associated with malignant transformation that are not apparent on ...
Zhao HM, Kong JC, Li YZ, Li W, Feng X.
europepmc   +2 more sources