Results 41 to 50 of about 109,853 (338)

Self- and Cross-Attention Enhanced Transformer for Visible and Thermal Infrared Hyperspectral Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Visible hyperspectral image (V-HSI) and thermal infrared hyperspectral image (TI-HSI) have been crucial data sources for land cover classification. V-HSI can directly provide information of land surface, such as shape, color, texture, and other features.
Enyu Zhao, Yongfang Su, Nianxin Qu, Yulei Wang, Caixia Gao, Jian Zeng   +5 more
doaj   +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

GETNET: A General End-to-end Two-dimensional CNN Framework for Hyperspectral Image Change Detection

, 2019
Change detection (CD) is an important application of remote sensing, which provides timely change information about large-scale Earth surface. With the emergence of hyperspectral imagery, CD technology has been greatly promoted, as hyperspectral data ...
Du, Qian, Fellow, Fellow, IEEE, IEEE, IEEE, Li, Xuelong, Member, Senior, Wang, Qi, Yuan, Zhenghang   +9 more
core   +1 more source

Deep learning in remote sensing: a review [PDF]

, 2017
Standing at the paradigm shift towards data-intensive science, machine learning techniques are becoming increasingly important. In particular, as a major breakthrough in the field, deep learning has proven as an extremely powerful tool in many fields ...
Fraundorfer, Friedrich, Mou, Lichao, Tuia, Devis, Xia, Gui-Song, Xu, Feng, Zhang, Liangpei, Zhu, Xiao Xiang   +6 more
core   +4 more sources

Hyperspectral estimation of chlorophyll content in jujube leaves: integration of derivative processing techniques and dimensionality reduction algorithms

Frontiers in Plant Science, 2023
The leaf chlorophyll content (LCC) of vegetation is closely related to photosynthetic efficiency and biological activity. Jujube (Ziziphus jujuba Mill.) is a traditional economic forest tree species.
Nigela Tuerxun, Nigela Tuerxun, Jianghua Zheng, Jianghua Zheng, Renjun Wang, Renjun Wang, Lei Wang, Liang Liu, Liang Liu   +8 more
doaj   +1 more source

Machine learning regression on hyperspectral data to estimate multiple water parameters

, 2018
In this paper, we present a regression framework involving several machine learning models to estimate water parameters based on hyperspectral data. Measurements from a multi-sensor field campaign, conducted on the River Elbe, Germany, represent the ...
Keller, Sina, Maier, Philipp M.
core   +1 more source

Hyperspectral pan-sharpening: a variational convex constrained formulation to impose parallel level lines, solved with ADMM

, 2014
In this paper, we address the issue of hyperspectral pan-sharpening, which consists in fusing a (low spatial resolution) hyperspectral image HX and a (high spatial resolution) panchromatic image P to obtain a high spatial resolution hyperspectral image ...
de Vieilleville, François, Grizonnet, Manuel, Huck, Alexis, Weiss, Pierre   +3 more
core   +1 more source

Fusion of UAV hyperspectral and satellite multispectral data for quasi-hyperspectral data simulation and wetland land cover classification

Geo-spatial Information Science
Accurate wetland classification demands high spectral detail and large-area coverage – capabilities that neither satellite multispectral data (limited spectral resolution) nor unmanned aerial vehicle (UAV) hyperspectral data (limited spatial coverage ...
Cong Shen, Yaqin Fang, Shaoyi Wang, Zixiao Liu, Xiaobin Cai, Zhiwei Ouyang, Liqiao Tian   +6 more
doaj   +1 more source

Robust hyperspectral image classification with rejection fields

, 2015
In this paper we present a novel method for robust hyperspectral image classification using context and rejection. Hyperspectral image classification is generally an ill-posed image problem where pixels may belong to unknown classes, and obtaining ...
Bioucas-Dias, Jose, Condessa, Filipe, Kovacevic, Jelena   +2 more
core   +1 more source

Further results on dissimilarity spaces for hyperspectral images RF-CBIR [PDF]

, 2013
Content-Based Image Retrieval (CBIR) systems are powerful search tools in image databases that have been little applied to hyperspectral images. Relevance feedback (RF) is an iterative process that uses machine learning techniques and user's feedback to ...
Datcu, Mihai, Graña, Manuel, Veganzones, Miguel Angel   +2 more
core   +3 more sources