Image Processing, Machine Learning and Geometric Modelling for the 3D Representation of Solar Features
Image Processing, Machine Learning and Geometric Modelling for the 3D Representation of Solar Features
批准号:
EP/F022948/1
负责人:
Rami Qahwaji
金额:
$37.38万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2008
资助国家:
英国
项目状态:
已结题
起止时间:
2008 至 --
中文摘要
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英文摘要
Space weather is an emerging subject that includes studies of solar activities and eruptions that affect the space between the planets and in particular on and around the Earth. Space weather is of growing significance to mankind for two reasons: firstly it affects life on Earth and secondly extremes of space weather affect communications and power systems, on which we are becoming more and more reliant. It is well known that certain solar features, seen as 2D projections in images of the sun, are highly correlated with the solar activities responsible for space weather and the purpose of this project is to construct the first 3D catalogue of the structures of such features. Such a catalogue will provide the opportunity to develop new indexes for the forecast of solar activities, needed since the present indexes are not reliable. We will use existing solar images captured at different wavelengths from both space and ground sources (i.e. the SOHO satellite and the Meudon Paris observatory) and we will include future data from the STEREO space mission when it becomes available. The solar features of interest in this project are sunspots, active regions and filaments and the 3D catalogue will be created using automated computer recognition of solar features based on multi-scale 2D feature extraction from solar images at multiple wavelengths (different wavelengths show the shapes of features at different heights). The automated system will analyse these extracted solar features to obtain parameters that will be used to create corresponding 3D models. The 3D models will provide physical and visual descriptions for the features of interest, which will be more complete than text-based descriptions and could require less computer storage than 2D image segmentations of the features of interest. This project is also a real convergence between 2D-based image processing and machine learning and 3D-based geometric modelling and we hope that the technology developed will be useful for other applications that may benefit from such interface.
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A new technique for the calculation and 3D visualisation of magnetic complexities on solar satellite images
太阳卫星图像上磁复杂性计算和 3D 可视化的新技术
DOI:
10.1007/s00371-010-0418-1
发表时间:
2010
期刊:
The Visual Computer
影响因子:
--
作者:
[Ahmed O]
通讯作者:
Ahmed O
DOI:
10.1007/s11207-011-9859-6
发表时间:
2011-09
期刊:
Solar Physics
影响因子:
2.8
作者:
[C. Verbeeck;P. Higgins;T. Colak;F. Watson;V. Delouille;B. Mampaey;R. Qahwaji]
通讯作者:
C. Verbeeck;P. Higgins;T. Colak;F. Watson;V. Delouille;B. Mampaey;R. Qahwaji
DOI:
10.1007/s11207-011-9880-9
发表时间:
2011-11
期刊:
Solar Physics
影响因子:
2.8
作者:
[T. Colak;R. Qahwaji]
通讯作者:
T. Colak;R. Qahwaji
A Multi-Wavelength Analysis of Active Regions and Sunspots by Comparison of Automated Detection Algorithms
通过自动检测算法比较对活动区域和太阳黑子进行多波长分析
DOI:
10.48550/arxiv.1109.0473
发表时间:
2011
期刊:
影响因子:
--
作者:
[Verbeeck C]
通讯作者:
Verbeeck C
DOI:
10.1007/s11207-011-9896-1
发表时间:
2013-03-01
期刊:
SOLAR PHYSICS
影响因子:
2.8
作者:
[Ahmed, Omar W., Qahwaji, Rami, Bloomfield, D. Shaun]
通讯作者:
Bloomfield, D. Shaun
共 6 条
国内基金
海外基金
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批准号:82373900
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项目类别:面上项目
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资助金额:48万元
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批准年份:2023
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负责人:王媛
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依托单位:
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批准号:82104210
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项目类别:青年科学基金项目(C类)
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批准年份:2021
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负责人:丰涛
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依托单位: