太阳局部高分辨观测像的日球坐标自动标定
An automatic approach of mapping the solar high-resolution image to Helioprojective-Cartesian coordinates system
查看参考文献15篇
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文摘
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观测图像的日球坐标标定通常是处理太阳局部高分辨观测像的第一个步骤,但这也一直是很多太阳物理学家面临的困难.本文应用尺度不变特征变换来提取特征匹配点,提出了一种将局部高分辨光球和色球图像与空间/地面全日面像自动匹配以确定其视场在日球坐标系位置的方法.同时还总结了一套有针对性的图像预处理方案和流程,用于提高特征点检测的准确度和增加匹配点对数量,从而成功地实现了新真空太阳望远镜(New Vacuum Solar Telescope, NVST)的氧化钛(titanium dioxide, TiO)波段与太阳动力学天文台(Solar Dynamics Observatory, SDO)日震磁像仪(helioseismic and magnetic imager, HMI)连续谱、Hα波段与全球日震网(Global Oscillation Network Group, GONG)或者太阳动力学天文台/大气成像仪(atmospheric imaging assembly, AIA)304 A波段的图像配准.最终结果用SDO标准关键字记录在标定后的普适图像传输系统(flexible image transport system, FITS)文件头中,以便使用通用的太阳软件包来进行各种后处理.这一工作实现了高分辨观测像的标准化日球坐标标定,为太阳物理学家更好地使用高分辨观测数据提供了极大的便利,从而提高了数据利用率和科学产出. |
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其他语种文摘
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The ground-based solar high-resolution observation usually only covers a small part of the solar disk, so determining the field of view position of an observed image on the Helioprojective-Cartesian coordinates is the first step in data processing. In the present, most solar physicists manually adjust parameters by trial and error to complete this step, because the mapping information may not be included in the flexible image transport system (FITS) header of a raw image. The manual approach cannot guarantee the accuracy. It is inefficient and has plagued many solar physicists. In this paper, we propose an automatic mapping approach by registering a high-resolution image to a standard calibrated solar full disk using image preprocessing and scale-invariant feature transform (SIFT) technology. Following steps are included. (1) Downsampling and blurring a high-resolution image to roughly fit the scale and the resolution of its corresponding full disk image; (2) scaling the gray level to 256 by local minimum and maximum to meet the requirements of applying the standard OpenCV SIFT processing package; (3) removing the limb-darkening of the reference full disk image with Cartesian to polar coordinate transform method; (4) detecting the feature points by SIFT on both high-resolution and full disk images; (5) matching corresponding point pairs by fast library for approximate nearest neighbors (FLANN); (6) calculating translation, rotation and scale parameters by random sample consensus (RANSAC); (7) recording the registration results in FITS header with standard keywords of the Solar Dynamics Observatory (SDO) image. These keywords can be automatically retrieved by the Solar SoftWare (SSW) system. With this approach, we have successfully registered both active region and quiet sun images observed by the titanium dioxide (TiO) band of the New Vacuum Solar Telescope (NVST) to the continuum of the helioseismic and magnetic imager (HMI) instrument on the SDO, and Hα active region images of NVST to the Global Oscillation Network Group (GONG) with high accuracy (0.25 arcsec for photosphere and 1 arcsec for chromosphere). If a high-resolution image shows bright structures, such as flares, the Hα image of NVST could be registered to 304 A image of the atmospheric imaging assembly (AIA) on SDO with the accuracy of 1 arcsec as well. In addition, the images observed by Hα blue/red wings (±0.7 A) of NVST, TiO of the Goode solar telescope (GST), Hα of the Optical and Near-infrared Solar Eruption Tracer (ONSET) are also successfully registered to SDO/HMI continuum or SDO/AIA 304 A full disk image. Iterative processing is applied to improve accuracy. An automatic SDO or GONG image downloading procedure and an extra interactive user interface are also integrated. This approach has met the requirement of mapping a highresolution image to the Helioprojective-Cartesian coordinates of full disk. Its weakness is that if a high-resolution image does not show high contrast, such as limb observation of photosphere or quiet sun of chromosphere, it is difficult to get a mapping result, because the whole strategy is based on image feature detection. The procedure will be merged into the observation system of NVST in the future, and will provide great convenience for the solar physicists to use the highresolution observation data. |
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来源
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科学通报
,2019,64(16):1738-1746 【核心库】
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DOI
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10.1360/N972019-00092
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关键词
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太阳高分辨图像
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全日面观测
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日球坐标系
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视场定标
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地址
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1.
中国科学院云南天文台, 昆明, 650216
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昆明理工大学信息工程与自动化学院, 昆明, 650504
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西南林业大学大数据与智能工程学院, 昆明, 650224
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语种
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中文 |
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文献类型
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研究性论文 |
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ISSN
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0023-074X |
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学科
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自动化技术、计算机技术 |
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基金
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国家自然科学基金
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文献收藏号
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CSCD:6511629
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