Results 71 to 80 of about 5,351 (266)

i.hyper: processing hyperspectral imagery in GRASS

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Abstract. Hyperspectral satellite missions such as EnMAP, PRISMA and Tanager have made imaging spectroscopy widely accessible, yet their heterogeneous formats, high dimensionality and demanding preprocessing requirements still hinder efficient scientific use.
Alen Mangafić, Tomaž Žagar
openaire   +2 more sources

Passive Color Imaging Through Macroscopic Strong Scattering Media

Advanced Science, EarlyView.
Light reflected from distant targets is severely attenuated and scattered by dense fog. A color‐channel‐simulated, independently exposed sCMOS array (CISA), combined with a passive colorful de‐scattering pipeline (PCDP), captures and reconstructs extremely weak target signals.
Renrui Wang, Xiaoyu Wang, Jianyu Wang, Zhiyu Yang, Xiangyang Ji   +4 more
wiley   +1 more source

Gudalur Spectral Target Detection (GST-D): A New Benchmark Dataset and Engineered Material Target Detection in Multi-Platform Remote Sensing Data

Remote Sensing, 2020
Target detection in remote sensing imagery, mapping of sparsely distributed materials, has vital applications in defense security and surveillance, mineral exploration, agriculture, environmental monitoring, etc. The detection probability and the quality
Sudhanshu Shekhar Jha, Rama Rao Nidamanuri   +1 more
doaj   +1 more source

Attention Residual Hybrid Network for Unmanned Aerial Vehicles Hyperspectral Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Unmanned aerial vehicle (UAV) hyperspectral images are endowed with abundant spectral information and spatial texture details, which are crucial for the precise classification and monitoring of terrestrial features.
Zhen Zhang, Linhuan Jiang, Bo-Hui Tang, Jianchen Liu, Qingwang Wang, Yabin Hu, Liang Huang, Zhitao Fu   +7 more
doaj   +1 more source

Flexible Integration of Structurally Diverse Spatial Multi‐Omics With AgaeSMO

Advanced Science, EarlyView.
AgaeSMO is a versatile and robust deep learning framework for flexible cross‐integration of spatial multi‐omics data. Leveraging a GATs network with a graph attention module, it learns joint embedding across diverse modalities, enabling integration of both structurally paired (e.g., spatial transcriptome‐epigenome, transcriptome‐proteome, transcriptome‐
Kunpeng Liu, Jinpo Su, Haotian Zhou, Yilin Shen, Mengke Qin, Yingjie Luo, Tiancai Wang, Zhenglin Chen, Yuanyuan Wang, Xiaokai Ma   +9 more
wiley   +1 more source

Automated Labeling of Materials in Hyperspectral Imagery [PDF]

IEEE Transactions on Geoscience and Remote Sensing, 2010
We present a technique for automatically labeling segmented hyperspectral imagery with semantically meaningful material labels. The technique compares the mean signatures of each image segment to a spectral library of known materials, and material labels are assigned to image segments according to the most similar library entry.
Brian D. Bue, Erzsébet Merényi, Beáta Csathó   +2 more
openaire   +1 more source

Potassium‐Impurity‐Modulated Self‐Trapped Excitons and Energy Transfer in Phase‐Separated, Mn4+‐Doped Li2HfF6

Advanced Science, EarlyView.
Li2HfF6 contains two spectroscopically distinct self‐trapped excitons (STEs): intrinsic STE1 and redshifted, K‐associated STE2. Potassium incorporation stabilizes STE2, which selectively sensitizes Mn4+ red emission. This work uncovers the often‐overlooked role of trace K impurities, demonstrating impurity modulation as an effective strategy for tuning
Menuka Adhikari, Thomas Murray, Cameron J. Lewis, Jett Wu, Hari Adhikari, Cheng Li, Jianguo Wen, Hui Wu, Zhiping Luo   +8 more
wiley   +1 more source

Mapping urban impervious surfaces from an airborne hyperspectral imagery using the object-oriented classification approach

MATEC Web of Conferences, 2017
The objective of this research is to explore the capabilities of the hyperspectral imagery in mapping the urban impervious objects and identifying the surface materials using an object-oriented approach.
Aguejdad Rahim, Serradj Aziz, Weber Christiane   +2 more
doaj   +1 more source

A COMPARISON OF LIDAR REFLECTANCE AND RADIOMETRICALLY CALIBRATED HYPERSPECTRAL IMAGERY [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016
In order to retrieve results comparable under different flight parameters and among different flight campaigns, passive remote sensing data such as hyperspectral imagery need to undergo a radiometric calibration.
A. Roncat, C. Briese, C. Briese, N. Pfeifer   +3 more
doaj   +1 more source

Snapshot Spatiotemporal‐Spectral Imaging Enabled by Joint Photonic Encoding

Advanced Science, EarlyView.
Spectra4D enables snapshot spatiotemporal‐spectral imaging by combining high‐speed DMD temporal modulation with CMOS‐integrated Fabry‐Pérot spectral encoding. From a single 2D measurement, a dual‐mask‐guided reconstruction network recovers multiple time‐resolved hyperspectral frames, enabling high‐fidelity observation of rapidly evolving spatial ...
Chunyu Chen, Junren Wen, Hao Sha, Chenying Yang, Ziyang Chen, Xiaochen Feng, Taiqin Chen, Wenzhen Zou, Xiangyu Chen, Xiangyang Ji, Guojun Liu, Yongbing Zhang   +11 more
wiley   +1 more source