HSOS全日面太阳像中太阳黑子的自动识别
Automatic Recognition of Sunspots in HSOS Full-Disk Solar Images
摘要：
本文介绍了在怀柔太阳观测站获得的太阳全日面光球图像中自动识别太阳黑子的方法。首先采用高斯算法对图像进行预处理。太阳黑子识别的形态Bot-hat操作和大津阈值。通过太阳黑子性质的标准，排除了太阳黑子的错误选择。此外，为了计算太阳黑子面积和太阳中心，太阳边缘提取的过程中，使用形态学关闭和腐蚀操作，并设置一个自适应阈值。太阳黑子识别的结果表明，该方法与人工方法检测到的太阳黑子数目有很好的一致性。太阳黑子的识别率为95%，错误率为1.2%。用该方法计算的太阳黑子面积与USAF/NOAA的黑子面积数据有很高的相关性（95%）。
英文摘要：
A procedure is introduced to recognise sunspots automatically in solar full-disk photosphere images obtained from Huairou Solar Observing Station, National Astronomical Observatories of China. The images are first pre-processed through Gaussian algorithm. Sunspots are then recognised by the morphological Bot-hat operation and Otsu threshold. Wrong selection of sunspots is eliminated by a criterion of sunspot properties. Besides, in order to calculate the sunspots areas and the solar centre, the solar limb is extracted by a procedure using morphological closing and erosion operations and setting an adaptive threshold. Results of sunspot recognition reveal that the number of the sunspots detected by our procedure has a quite good agreement with the manual method. The sunspot recognition rate is 95% and error rate is 1.2%. The sunspot areas calculated by our method have high correlation (95%) with the area data from USAF/NOAA.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
