It is of great interest and importance to study the variabilities of solar EUV, UV and X-ray irradiance in heliophysics, in Earth’s climate, and space weather applications. A careful study is required to identify, track, monitor and segment the different coronal features such as active regions (ARs), coronal holes (CHs), the background regions (BGs) and the X-ray bright points (XBPs) from spatially resolved full-disk images of the Sun. Variability of solar soft X-ray irradiance is studied for a period of 13 years (February 2007–March 2020, covers Solar Cycle 24), using the X-Ray Telescope on board the Hinode (Hinode/XRT) and GOES (1 – 8 Å). The full-disk X-ray images observed in Al_mesh filter from XRT are used, for the first time, to understand the solar X-ray irradiance variability measured, Sun as a star, by GOES instrument. An algorithm in Python has been developed and applied to identify and segment coronal X-ray features (ARs, CHs, BGs, and XBPs) from the full-disk soft X-ray observations of Hinode/XRT. The segmentation process has been carried out automatically based on the intensity level, morphology and sizes of the X-ray features. The total intensity, area, and contribution of ARs/CHs/BGs/XBPs features were estimated and compared with the full-disk integrated intensity (FDI) and GOES (1 – 8 Å) X-ray irradiance measurements. The XBPs have been identified and counted automatically over the full disk to investigate their relation to solar magnetic cycle. The total intensity of ARs/CHs/BGs/XBPs/FD regions are compared with the GOES (1 – 8 Å) X-ray irradiance variations. We present the results obtained from Hinode/XRT full-disk images (in Al_mesh filter) and compare the resulting integrated full-disk intensity (FDI) with GOES X-ray irradiance. The X-ray intensity measured over ARs/CHs/BGs/XBPs/FD is well correlated with GOES X-ray flux. The contributions of the segmented X-ray features to FDI and X-ray irradiance variations are determined. It is found that the background and active regions have a greater impact on the X-ray irradiance fluctuations. The mean contribution estimated for the whole observed period of the background regions (BGs) will be around \(65\pm10.97\%\), whereas the ARs, XBPs and CHs are \(30\pm11.82\%\), \(4\pm1.18\%\) and \(1\pm0.52\%\), respectively, to total solar X-ray flux. We observed that the area and contribution of ARs and CHs varies with the phase of the solar cycle, whereas the BGs and XBPs show an anti-correlation. We find that the area of the coronal features is highly variable suggesting that their area has to be taken into account in irradiance models, in addition to their intensity variations. The time series results of XBPs suggest for an existence of anti-correlation between the number of XBPs and the sunspot numbers. It is also important to consider both the number variation and the contribution of XBPs in the reconstruction of total solar X-ray irradiance variability.

研究太阳EUV，紫外线和X射线辐照度在太阳物理学，地球气候和太空天气应用中的变化具有极大的兴趣和重要性。需要仔细研究以从空间分辨力中识别，跟踪，监视和分割不同的冠状特征，例如活动区域（AR），冠状孔（CH），背景区域（BG）和X射线亮点（XBP） Sun的全磁盘映像。使用Hinode（Hinode / XRT）和GOES上的X射线望远镜对太阳软X射线辐照度的变化进行了为期13年的研究（2007年2月至2020年3月，涵盖太阳周期24）（1-8）一种）。首次使用在XRT的Al_mesh滤镜中观察到的全盘X射线图像，了解通过GOES仪器测量的太阳X射线辐照度变异性（以太阳为恒星）。已经开发了Python中的算法，并将其应用于从Hinode / XRT的全盘软X射线观测中识别和分割冠状X射线特征（AR，CH，BG和XBP）。分割过程是根据X射线特征的强度级别，形态和大小自动进行的。估计了ARs / CHs / BGs / XBPs功能的总强度，面积和贡献，并将其与全盘综合强度（FDI）和GOES（1 – 8Å）X射线辐照度测量结果进行了比较。XBP已被识别并自动在整个磁盘上计数，以研究它们与太阳磁循环的关系。将ARs / CHs / BGs / XBPs / FD区域的总强度与GOES（1 – 8Å）X射线辐照度变化进行比较。我们介绍了从Hinode / XRT全盘图像（在Al_mesh滤镜中）获得的结果，并将所得的集成全盘强度（FDI）与GOES X射线辐照度进行了比较。在ARs / CHs / BGs / XBPs / FD上测量的X射线强度与GOES X射线通量密切相关。确定分段的X射线特征对FDI和X射线辐照度变化的贡献。发现背景区域和有源区域对X射线辐照度波动具有更大的影响。在整个背景区域（BG）的整个观察期间内估计的平均贡献约为 我们介绍了从Hinode / XRT全盘图像（在Al_mesh滤镜中）获得的结果，并将所得的集成全盘强度（FDI）与GOES X射线辐照度进行了比较。在ARs / CHs / BGs / XBPs / FD上测量的X射线强度与GOES X射线通量密切相关。确定分段的X射线特征对FDI和X射线辐照度变化的贡献。发现背景区域和有源区域对X射线辐照度波动具有更大的影响。在整个背景区域（BG）的整个观察期间内估计的平均贡献约为 我们介绍了从Hinode / XRT全盘图像（在Al_mesh滤镜中）获得的结果，并将所得的集成全盘强度（FDI）与GOES X射线辐照度进行了比较。在ARs / CHs / BGs / XBPs / FD上测量的X射线强度与GOES X射线通量密切相关。确定分段的X射线特征对FDI和X射线辐照度变化的贡献。发现背景区域和有源区域对X射线辐照度波动具有更大的影响。在整个背景区域（BG）的整个观察期间内估计的平均贡献约为 发现背景区域和有源区域对X射线辐照度波动具有更大的影响。在整个背景区域（BG）的整个观察期间内估计的平均贡献约为 发现背景区域和有源区域对X射线辐照度波动具有更大的影响。在整个背景区域（BG）的整个观察期间内估计的平均贡献约为\（65 \ pm10.97 \％\），而AR，XBP和CH分别是\（30 \ pm11.82 \％\），\（4 \ pm1.18 \％\）和\（1 \ pm0。 52 \％\）分别为总太阳X射线通量。我们观察到，ARs和CHs的面积和贡献随太阳周期的相位而变化，而BGs和XBPs显示出反相关。我们发现冠状特征的面积变化很大，这表明除了强度变化外，在辐照模型中还必须考虑它们的面积。XBP的时间序列结果表明XBP数量与黑子数之间存在反相关。在重建总太阳X射线辐照度变异性时，还应考虑XBP的数量变化和贡献，这一点也很重要。