| 其他摘要 | The corona is the outermost layer of the Sun's atmosphere, consisting of thin, highly ionized, and hot plasma. The maximum brightness of the corona is only a few millionths of that of the photosphere, making it obscured in daylight and invisible most of the time. The only exception is during total solar eclipses when the Moon completely blocks light from the photosphere, and Earth's atmospheric scattering is weak enough for us to have a chance to observe the corona directly. The coronagraph is a specialized telescope used to observe the solar corona outside of total solar eclipses. An internally-occultated coronagraph uses an occulter inside the telescope to block the image of the Sun and provides strict suppression of stray light, enabling observations of the corona at high altitudes. The stray light inside the coronagraph can be categorized as fixed and variable. Variable stray light changes over time and environmental cleanliness, while fixed stray light remains constant. Variable stray light is primarily caused by the scattering of dust particles on the surface of the objective lens. It results in the formation of a variable scattering background on the coronal image, which changes with the level of dust. This not only obscures the faint coronal structure but also impacts the intensity calibration of the coronal image. This scattering background can be reduced by frequent cleaning of the objective lens. However, in the long run, this can damage the ultra-smooth polished objective lens and cause additional stray light. This work is to correct the intensity of dust stray light. Based on the Lijiang coronagraph, we designed an experimental scheme to obtain information about the dust on the surface of the objective lens and its scattering background in the coronal images, and established two empirical models to describe the relationship between the scattering background and the dust. Based on these two models, we corrected the coronal images containing scattering background. In the data processing, to solve the alignment problem between the images, a new algorithm was designed and implemented for registering the coronal images. This work is not only an important step in the intensity calibration of coronal images but also enables the determination of the Heliocentric coordinates of coronal images, which greatly enhances the scientific value of the data. Different from previous theoretical models of dust stray light, we have for the first time obtained a quantitative relationship between the scattering background and objective dust through measured data, and established two empirical models. The first two-parameter model assumes a uniform distribution of dust on the surface of the objective lens and derives an isotropic scattering background. This background is only related to the heliocentric distance r and the total intensity of the scattering points I. The second three-parameter model takes into account the angular distribution of the scattering points. It utilizes the statistics of the sector segmentation of the image to determine the contribution of the scattering points to the scattering background in each direction. This model adds a new directional angle parameter of the scattering background theta to simulate the relationship between the dust and the scattering background, enabling the simulation of anisotropic scattering background. Correction of the coronal image is achieved by simulating a scattering background using the model and subtracting it from the original coronal image. This has a significant effect on the intensity correction of the inner coronal region, with a correction accuracy greater than 90%. This work effectively enhances the quality of coronal data, making the originally relatively weak coronal structure more prominent and clear, contributing to the discovery of coronal activity phenomena such as CMEs and jets. This step is also crucial in the high-precision calibration of coronal data, providing reliable data for the routine measurement of coronal magnetic fields in future large-scale ground-based coronagraphs. To solve the alignment problem of coronal images in data processing, statistical correlation and feature point matching methods are combined to register coronal images with space-based SDO/AIA standard images. After several preprocessing steps like polar coordinate transformation, segmentation, correlation, feature point extraction, feature point matching, and affine transformation, the image to be registered is updated. Continuously iterating the above steps, the rough registration of the two images was finally completed. This algorithm is not only applicable to the experimental data, but can also be widely applied to coronal devices. After registering coronal images with the same device, the Pearson correlation coefficient between the two reaches 0.999 or above. Registration between different devices can obtain the heliocentric coordinate system, achieving collaborative observation of multi device coronal data. In the future, we will continue to advance this research. Conduct coronagraph experiments at higher altitude Daocheng Observatory to obtain more accurate scattering background models. Improve the above registration model to increase the registration accuracy between different devices and accurately obtain the heliocentric coordinate system. In addition, we will also be committed to the development of large-diameter coronagraphs and conduct research on solar eruptions and solar magnetic field measurements based on Sino-foreign cooperation. |
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