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• W2950971852 abstract "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 pre-processing 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 high-resolution 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 high-resolution observation data." @default.
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• W2950971852 date "2019-05-09" @default.
• W2950971852 modified "2023-10-12" @default.
• W2950971852 title "An automatic approach of mapping the solar high-resolution image to Helioprojective-Cartesian coordinates system" @default.
• W2950971852 doi "https://doi.org/10.1360/n972019-00092" @default.
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