Full-disk Solar Images Research Articles

Attention-Based Deep Learning Model for Image Desaturation of SDO/AIA

The Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO) captures full-disk solar images in seven extreme ultraviolet wave bands. As a violent solar flare occurs, incoming photoflux may exceed the threshold of an optical imaging system, resulting in regional saturation/overexposure of images. Fortunately, the lost signal can be partially retrieved from non-local unsaturated regions of an image according to scattering and diffraction principle, which is well consistent with the attention mechanism in deep learning. Thus, an attention augmented convolutional neural network (AANet) is proposed to perform image desaturation of SDO/AIA in this paper. It is built on a U-Net backbone network with partial convolution and adversarial learning. In addition, a lightweight attention model, namely criss-cross attention, is embedded between each two convolution layers to enhance the backbone network. Experimental results validate the superiority of the proposed AANet beyond state-of-the-arts from both quantitative and qualitative comparisons.

The Solar Upper Transition Region Imager (SUTRI) Onboard the SATech-01 Satellite

The Solar Upper Transition Region Imager (SUTRI) onboard the Space Advanced Technology demonstration satellite (SATech-01), which was launched to a Sun-synchronous orbit at a height of ∼500 km in 2022 July, aims to test the on-orbit performance of our newly developed Sc/Si multi-layer reflecting mirror and the 2k×2k EUV CMOS imaging camera and to take full-disk solar images at the Ne vii 46.5 nm spectral line with a filter width of ∼3 nm. SUTRI employs a Ritchey–Chrétien optical system with an aperture of 18 cm. The on-orbit observations show that SUTRI images have a field of view of ∼ 41.′6 × 41.′6 and a moderate spatial resolution of ∼8″ without an image stabilization system. The normal cadence of SUTRI images is 30 s and the solar observation time is about 16 hr each day because the earth eclipse time accounts for about 1/3 of SATech-01's orbit period. Approximately 15 GB data is acquired each day and made available online after processing. SUTRI images are valuable as the Ne vii 46.5 nm line is formed at a temperature regime of ∼0.5 MK in the solar atmosphere, which has rarely been sampled by existing solar imagers. SUTRI observations will establish connections between structures in the lower solar atmosphere and corona, and advance our understanding of various types of solar activity such as flares, filament eruptions, coronal jets and coronal mass ejections.

SunMap: A Solar Image Processing Software for Obtaining Synoptic Maps

A new open-source software, called SunMap, has been developed to obtain synoptic maps in an easy and quick way from multiple full-disc solar images. Our objective is to provide a free and straightforward application for heliophysicists and geophysicists interested in generating solar synoptic maps. SunMap allows comparison of structures and patterns of solar activity over various periods. Thus, the short- and long-term evolution of solar regions of interest can be studied. To reach this goal, different solar images taken day by day are stored in a single map that uses a sequence of images and allows the positioning of each observable element on it. A simple comparison between a synoptic map generated by SunMap and another previously constructed map is presented to show the versatility of this new available software.

Solar Filament Detection Based on Improved DeepLab V3+

A novel solar filament detection method based on an improved DeepLab V3+ is proposed to address the low detection accuracy of small solar filaments in Hα full-disk solar images. First, the Xception structure of the backbone network is fine-tuned, and the low-level feature information of the filaments is added to the decoder module of the network to improve the utilization of the solar filament features. Second, the receptive field of dilated convolution is expanded, and the information utilization rate is increased via cascaded dilated convolution to improve the detection accuracy of the small solar filaments. In the decoder module, two depthwise separable convolutions are used instead of ordinary convolutions to reduce incomplete detections. Finally, a dense conditional random field is added to optimize the edge of the detection results. Experiments on a public data set comprising full-disk Hα images show that compared with the original Deeplab V3+ algorithm, the proposed method improves the mean pixel accuracy, mean intersection over union, and F1-score by 1.86%, 1.95%, and 2.18%, respectively, which also demonstrates its superiority over other existing solar filament detection algorithms.

Image Desaturation for SDO/AIA Using Mixed Convolution Network

The Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO) provides full-disk solar images with high temporal cadence and spatial resolution over seven extreme ultraviolet (EUV) wave bands. However, as violent solar flares happen, images captured in EUV wave bands may have saturation in active regions, resulting in signal loss. In this paper, we propose a deep learning model to restore the lost signal in saturated regions by referring to both unsaturated/normal regions within a solar image and statistical probability model of massive normal solar images. The proposed model, namely mixed convolution network (MCNet), is established over conditional generative adversarial network (GAN) and the combination of partial convolution (PC) and validness migratable convolution (VMC). These two convolutions were originally proposed for image inpainting. In addition, they are implemented only on unsaturated/valid pixels, followed by certain compensation to compensate the deviation of PC/VMC relative to normal convolution. Experimental results demonstrate that the proposed MCNet achieves favorable desaturated results for solar images and outperforms the state-of-the-art methods both quantitatively and qualitatively.

A first look at the submillimeter Sun with ALMA

We present the first full-disk solar images obtained with the Atacama Large Millimeter/submillimeter Array (ALMA) in Band 7 (0.86 mm; 347 GHz). In spite of the low spatial resolution (21″), several interesting results were obtained. During our observation, the sun was practically devoid of active regions. Quiet Sun structures on the disk are similar to those in Atmospheric Imaging Assembly images at 1600 Å and 304 Å, after the latter are smoothed to the ALMA resolution, as noted previously for Band 6 (1.26 mm) and Band 3 (3 mm) images; they are also similar to negative Hα images of equivalent resolution. Polar coronal holes, which are clearly seen in the 304 Å band and small Hα filaments, are not detectable at 0.86 mm. We computed the center-to-limb variation of the brightness temperature, Tb, in Band 7, as well as in Bands 6 and 3, which were obtained during the same campaign, and we combined them to a unique curve of Tb(log μ100), where μ100 is the cosine of the heliocentric angle reduced to 100 GHz. Assuming that the absolute calibration of the Band 3 commissioning observations is accurate, we deduced a brightness temperature at the center of the disk of 6085 K for Band 7, instead of the value of 5500 K, extrapolated from the recommended values for Bands 3 and 6. More importantly, the Tb(log μ100) curve flattens at large values of μ100, and so does the corresponding Te(log τ100) at large τ100. This is probably an indication that we are approaching the temperature minimum.

The Solar ALMA Science Archive (SALSA)

In December 2016, the Atacama Large Millimeter/submillimeter Array (ALMA) carried out the first regular observations of the Sun. These early observations and the reduction of the respective data posed a challenge due to the novelty and complexity of observing the Sun with ALMA. The difficulties with producing science-ready, time-resolved imaging products in a format familiar to and usable by solar physicists based on the measurement sets delivered by ALMA had limited the availability of such data to this point. With the development of the Solar ALMA Pipeline, it has now become possible to routinely reduce such data sets. As a result, a growing number of science-ready solar ALMA data sets are now offered in the form of the Solar ALMA Science Archive (SALSA). So far, SALSA contains primarily time series of single-pointing interferometric images at cadences of one or two seconds, accompanied by the respective single-dish full-disc solar images. The data arrays are provided in FITS format. We also present the first version of a standardised header format that accommodates future expansions and fits within the scope of other standards including the ALMA Science Archive itself and SOLARNET. The headers include information designed to aid the reproduction of the imaging products from the raw data. Links to co-observations, if available, with a focus on those of the Interface Region Imaging Spectrograph, are also provided. SALSA is accompanied by the Solar ALMA Library of Auxiliary Tools (SALAT), which contains Interactive Data Language and Python routines for convenient loading and a quick-look analysis of SALSA data.

ALMA small-scale features in the quiet Sun and active regions

Aims. The main aim of the present analysis is to decipher (i) the small-scale bright features in solar images of the quiet Sun and active regions obtained with the Atacama Large Millimeter/submillimeter Array (ALMA) and (ii) the ALMA correspondence of various known chromospheric structures visible in the Hα images of the Sun. Methods. Small-scale ALMA bright features in the quiet Sun region were analyzed using single-dish ALMA observations (1.21 mm, 248 GHz) and in an active region using interferometric ALMA measurements (3 mm, 100 GHz). With the single-dish observations, a full-disk solar image is produced, while interferometric measurements enable the high-resolution reconstruction of part of the solar disk, including the active region. The selected quiet Sun and active regions are compared with the Hα (core and wing sum), EUV, and soft X-ray images and with the magnetograms. Results. In the quiet Sun region, enhanced emission seen in the ALMA is almost always associated with a strong line-of-sight magnetic field. Four coronal bright points were identified, while other small-scale ALMA bright features are most likely associated with magnetic network elements and plages. In the active region, in 14 small-scale ALMA bright features randomly selected and compared with other images, we found five good candidates for coronal bright points, two for plages, and five for fibrils. Two unclear cases remain: a fibril or a jet, and a coronal bright point or a plage. A comparison of the Hα core image and the 3 mm ALMA image of the analyzed active region showed that the sunspot appears dark in both images (with a local ALMA radiation enhancement in sunspot umbra), the four plage areas are bright in both images and dark small Hα filaments are clearly recognized as dark structures of the same shape also in ALMA.

Mingantu Spectral Radioheliograph for Solar and Space Weather Studies

The Chinese Spectral Radioheliograph (CSRH) covering 400 MHz-15 GHz frequency range was constructed during 2009–2016 in Mingantu Observing Station, National Astronomical Observatories, Chinese Academy of Sciences at Zhengxiangbaiqi, Inner Mongolia of China. The CSRH is renamed as MingantU SpEctral Radioheliograph (MUSER) after its accomplishment. Currently, MUSER consists of two arrays spreading over three spiral-shaped arms. The maximum baseline length is ∼3 km in both east-west and north-south directions. The MUSER array configuration is optimized to meet the needs of observing the full-disk Sun over ultrawide wavebands with images of high temporal, spatial and spectral resolutions and high dynamic range. The low frequency array, called MUSER-I, covers 400 MHz-2.0 GHz with 40 antennas of 4.5-m-diameter each and the high frequency array, called MUSER-II, covers 2–15 GHz with 60 antennas of 2-m-diameter each. The MUSER-I can obtain full-disk solar radio images in 64 frequency channels with a time cadence of 25 ms and a spatial resolution of 51.6″ to 10.3″ (corresponding to the frequency range 400 MHz to 2 GHz), whereas the MUSER-II can obtain full-disk solar images in 520 channels with a time cadence of 206.25 ms and a spatial resolution of 10.3″ to 1.3 (corresponding to the frequency range 2 to 15 GHz). A dynamic range of 25 dB can be obtained with snapshot images produced with the MUSER. An extension of MUSER in the further lower frequency range covering 30–400 MHz with an array of 224 logarithm-periodic dipole antennas (LPDAs) has been approved and will be completed during the next 4 years. The MUSER, as a dedicated solar instrument, has the following advantages providing simultaneous images over a wide frequency range with a unique high temporal-spatial-spectral resolutions; high-performing ultrawide-band dual-polarization feeds for wide-band signal collection; advanced high data-rate, large-scale digital correlation receiver for multiple-frequency and faster snapshot observations; and applications of new technologies such as using optical fiber to obtain remote antenna and wide-band analog signal transmission. The MUSER thus provides a unique opportunity to measure solar magnetic fields and trace dynamic evolution of energetic electrons in several radio frequencies, which, in turn, will help to have better understandings of the origin of various solar activities and the basic drivers of space weather.

Image Desaturation for SDO/AIA Using Deep Learning

The Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO) (launched in February 2010) provides uninterrupted full-disk solar images over 10 wavebands. In the case of violent solar flares, saturation would happen to SDO/AIA images in their core regions, which leads to signal loss, hindering us to understand physical mechanism behind solar flares. This paper introduces a deep learning based image restoration model which can recover signal of saturation region by referring to other normal/valid region within an image. The proposed model, namely PCGAN, combines partial convolution (PC) and conditional generative adversarial network (GAN). The PC module was originally designed for image inpainting, for repairing images with scratches and holes. In addition, a new comprehensive loss function consists of an adversarial loss, a pixel reconstruction loss, a gradient loss, a perceptual loss, a style loss and a total variation loss. Moreover, for validating the proposed model, a new dataset consisting of paired saturated and normal SDO/AIA images is established. Experimental results demonstrate that the proposed PCGAN can get appealing desaturated solar images with respect to both objective and subjective validations.

A coarse-to-fine strategy for the registration of the multi-wavelength high-resolution solar images

The registration of multi-wavelength high-resolution solar images is an important task in the research of solar physics. This paper proposed a coarse-to-fine strategy to realize the accurate registration of high-resolution photospheric images and chromospheric images observed by the New Vacuum Solar Telescope (NVST) whose field-of-view is about 2′ ∼ 3′, and the spatial resolution can reach 0.1″ after image reconstruction. In this strategy, the full-disk solar images with relatively lower resolution taken by other space- or ground-based telescopes are taken as transition images, and the Fourier-Merlin transform, Template matching and a local statistical information based algorithm are used in combination. After registration, the geometric transformation between multi-wavelength images of NVST are corrected at the level of sub-arcseconds, including the rotation, scaling and translation relations. Two sets of data observed in active regions (i.e., the NOAA 11982 and the NOAA 12673) are used to illustrate our method step by step. The result shows that the registration accuracy can reach less than 1″. Moreover, this work also has facilitated the combination of high-resolution observations of NVST with the continuum, ultraviolet passbands and magnetic field observations of the Solar Dynamic Observation (SDO), which is highly beneficial to the multi-instrument joint measurement of solar activities.

Flat-fielding of Full-disk Solar Images with a Gaussian-type Diffuser

Full-disk solar chromospheric and photospheric images are widely used to monitor solar activity. Flat-fielding is a basic step during scientific data production. Here, a Gaussian-type diffuser is used to measure the flat-field of full-disk solar chromospheric and photospheric images. The effectiveness of the method is verified by theoretical simulation and practical measurement. First, the uniformity of the light source generated by the Gaussian diffuser and the sunlight, with a field of view the same as the full-disk solar image, is calculated. The full width at half maximum (FWHM) of the scatter angle of the Gaussian diffuser is one degree, such that the light source presents a Gaussian distribution. After the correction of the Gaussian background, the uniformity of the area light source is 99.6%, which can be regarded as a uniform area light source. Second, experiments are conducted on full-disk solar telescopes at Huairou solar observing station and Yangbajing station. The diffuser covers the entire entrance aperture when taking flat-field frames. Through qualitative and quantitative analysis of experimental results, it is confirmed that a revised flat-field frame can modify uniformity caused by various aspects of the telescope, including vignetting, non-uniformities of filters, and contamination of optical components.

Solar Filament Recognition Based on Deep Learning

The paper presents a reliable method using deep learning to recognize solar filaments in H-alpha full-disk solar images automatically. This method cannot only identify filaments accurately but also minimize the effects of noise points of the solar images. Firstly, a raw filament dataset is set up, consisting of tens of thousands of images required for deep learning. Secondly, an automated method for solar filament identification is developed using the U-Net deep convolutional network. To test the performance of the method, a dataset with 60 pairs of manually corrected H-alpha images is employed. These images are obtained from the Big Bear Solar Observatory/Full-Disk H-alpha Patrol Telescope (BBSO/FDHA) in 2013. Cross-validation indicates that the method can efficiently identify filaments in full-disk H-alpha images.

Filling Factors of Sunspots in SODISM Images

The calculated filling factors (FFs) for a feature reflect the fraction of the solar disc covered by that feature, and the assignment of reference synthetic spectra. In this paper, the FFs, specified as a function of radial position on the solar disc, are computed for each image in a tabular form. The filling factor (FF) is an important parameter and is defined as the fraction of area in a pixel covered with the magnetic field, whereas the rest of the area in the pixel is field-free. However, this does not provide extensive information about the experiments conducted on tens or hundreds of such images. This is the first time that filling factors for SODISM images have been catalogued in tabular formation. This paper presents a new method that provides the means to detect sunspots on full-disk solar images recorded by the Solar Diameter Imager and Surface Mapper (SODISM) on the PICARD satellite. The method is a totally automated detection process that achieves a sunspot recognition rate of 97.6%. The number of sunspots detected by this method strongly agrees with the NOAA catalogue. The sunspot areas calculated by this method have a 99% correlation with SOHO over the same period, and thus help to calculate the filling factor for wavelength (W.L.) 607nm.

Filling Factors of Sunspots in SODISM Images

The calculated filling factors (FFs) for a feature reflect the fraction of the solar disc covered by that feature, and the assignment of reference synthetic spectra. In this paper, the FFs, specified as a function of radial position on the solar disc,are computed for each image in a tabular form. The filling factor (FF) is an important parameter and is defined as the fraction of area in a pixel covered with the magnetic field, whereas the rest of the area in the pixel is field-free. However, this does not provide extensive information about the experiments conducted on tens or hundreds of such images. This is the first time that filling factors for SODISM images have been catalogued in tabular formation. This paper presents a new method that provides the means to detect sunspots on full-disk solar images recorded by the Solar Diameter Imager and Surface Mapper (SODISM) on the PICARD satellite. The method is a totally automated detection process that achieves a sunspot recognition rate of 97.6%. The number of sunspots detected by this method strongly agrees with the NOAA catalogue. The sunspot areas calculated by this method have a 99% correlation with SOHO over the same period, and thus help to calculate the filling factor for wavelength (W.L.) 607nm.

First high-resolution look at the quiet Sun with ALMA at 3mm

We present an overview of high-resolution quiet Sun observations, from disk center to the limb, obtained with the Atacama Large millimeter and sub-millimeter Array (ALMA) at 3 mm. Seven quiet-Sun regions were observed at a resolution of up to 2.5″ by 4.5″. We produced both average and snapshot images by self-calibrating the ALMA visibilities and combining the interferometric images with full-disk solar images. The images show well the chromospheric network, which, based on the unique segregation method we used, is brighter than the average over the fields of view of the observed regions by ∼305 K while the intranetwork is less bright by ∼280 K, with a slight decrease of the network/intranetwork contrast toward the limb. At 3 mm the network is very similar to the 1600 Å images, with somewhat larger size. We detect, for the first time, spicular structures, rising up to 15″ above the limb with a width down to the image resolution and brightness temperature of ∼1800 K above the local background. No trace of spicules, either in emission or absorption, is found on the disk. Our results highlight the potential of ALMA for the study of the quiet chromosphere.

Identification of Solar Activities Based on Heliophysics Event Knowledgebase

Solar image consists of obvious regions of solar activities and peaceful regions of no activity. Identifying effective solar active areas from solar image is a typical application of image-processing technology in astronomical research. Benefiting from real-time solar observation data provided by Heliophysics Event Knowledgebase (HEK) of Solar Dynamics Observatory (SDO), this paper presents a method of solar activity identification based on HEK. In this method, we gather data of six kinds of solar activities (time, location, and area) and establish a multiscale transformation model for the full-disk solar image of the corresponding time. Combining both location data and area data, we design different gradient thresholds to segment different solar activities’ regions. Two kinds of boundary-identification methods are used to locate and recognize solar activities’ regions, respectively. Furthermore, we study the correlation of the characteristic parameters (six kinds of solar activities’ data) of solar image and get the best combination of the characteristic parameters of each solar activity. The method in the paper provides precise positioning and efficient identification of solar activities, which lays the foundation for further work. In addition to that, extracting specific combination of features from different solar activities’ regions can provide a feasible way to build a streamlined image feature set for content-based image retrieval (CBIR) systems.

First analysis of solar structures in 1.21 mm full-disc ALMA image of the Sun

Context.Various solar features can be seen in emission or absorption on maps of the Sun in the millimetre and submillimetre wavelength range. The recently installed Atacama Large Millimetre/submillimetre Array (ALMA) is capable of observing the Sun in that wavelength range with an unprecedented spatial, temporal and spectral resolution. To interpret solar observations with ALMA, the first important step is to compare solar ALMA maps with simultaneous images of the Sun recorded in other spectral ranges.Aims.The first aim of the present work is to identify different structures in the solar atmosphere seen in the optical, infrared, and EUV parts of the spectrum (quiet Sun, active regions, prominences on the disc, magnetic inversion lines, coronal holes and coronal bright points) in a full-disc solar ALMA image. The second aim is to measure the intensities (brightness temperatures) of those structures and to compare them with the corresponding quiet Sun level.Methods.A full-disc solar image at 1.21 mm obtained on December 18, 2015, during a CSV-EOC campaign with ALMA is calibrated and compared with full-disc solar images from the same day in Hαline, in He I1083 nm line core, and with various SDO images (AIA at 170 nm, 30.4 nm, 21.1 nm, 19.3 nm, and 17.1 nm and HMI magnetogram). The brightness temperatures of various structures are determined by averaging over corresponding regions of interest in the calibrated ALMA image.Results.Positions of the quiet Sun, active regions, prominences on the disc, magnetic inversion lines, coronal holes and coronal bright points are identified in the ALMA image. At the wavelength of 1.21 mm, active regions appear as bright areas (but sunspots are dark), while prominences on the disc and coronal holes are not discernible from the quiet Sun background, despite having slightly less intensity than surrounding quiet Sun regions. Magnetic inversion lines appear as large, elongated dark structures and coronal bright points correspond to ALMA bright points.Conclusions.These observational results are in general agreement with sparse earlier measurements at similar wavelengths. The identification of coronal bright points represents the most important new result. By comparing ALMA and other maps, it was found that the ALMA image was oriented properly and that the procedure of overlaying the ALMA image with other images is accurate at the 5 arcsec level. The potential of ALMA for physics of the solar chromosphere is emphasised.

Automatic detection of solar features in HSOS full-disk solar images using guided filter

A procedure is introduced for the automatic detection of solar features using full-disk solar images from Huairou Solar Observing Station (HSOS), National Astronomical Observatories of China. In image preprocessing, median filter is applied to remove the noises. Guided filter is adopted to enhance the edges of solar features and restrain the solar limb darkening, which is first introduced into the astronomical target detection. Then specific features are detected by Otsu algorithm and further threshold processing technique. Compared with other automatic detection procedures, our procedure has some advantages such as real time and reliability as well as no need of local threshold. Also, it reduces the amount of computation largely, which is benefited from the efficient guided filter algorithm. The procedure has been tested on one month sequences (December 2013) of HSOS full-disk solar images and the result shows that the number of features detected by our procedure is well consistent with the manual one.

The measurement of flat fields and polarization offset from the routine observation data of a solar rotation

The correction of flat fields and polarization offset is a necessary step in the reduction of the full-disk solar observing data. The general used methods of the measurement of flat fields are summarized as follows. The first one is realized by randomly moving the solar telescope and making an average of thousands of observed images of the quiet region near the disk center, which is adopted by the large aperture solar telescopes with a small field-of-view. The second one is to shift the solar images with slightly different pointings, which is mostly used in the full-disk solar images. The third method is to use a diffuser to generate the uniform light source and it can be used in the full-disk solar images, too. Observing the nearby continuum of the selected working spectral line is generally used to obtain the polarization offset. It is worth to mention that, all these methods need special calibration observing mode and occupy the valuable scientific observation time. In the paper, we propose a new method to derive the flat fields and polarization offset from the routine observing data. Assuming that the flat fields and polarization offset do not change during a solar rotation, we firstly got the formula which can be used in the calculation of flat fields and polarization offset in the case of the ideal and real telescope guiding and pointing accuracy. The core algorithm in the formula is median process. Moreover, we obtained the flat fields and the crosstalk from Stokes I to Q , U and V using the above mentioned formula from series of the routine observed monochromatic image and Stokes Q / I , U / I and V / I images belonging to the Carrington Rotation 2144 observed by Huairou Solar Observing Station. The derived flat fields could not only reflect the small-scale dirty points but also the large-scale non-uniform pattern from the whole telescope system, which can be removed after the flat-fielding process. The distribution of the resulting Stokes V / I offset from Stokes I to V seems to be a Saddle surface, while that of the Stokes Q / I and U / I from I to Q , U is an upside-down bell shape. In order to evaluate the validity of the correction of the polarization offset we choose a quiet region near the solar limb as an example. The averaged value of Stokes V / I , Q / I and U / I in the region after polarization offset correction is −0.8×10−4, 0.9×10−4, 1.3×10−4, while that before correction is −6.8×10−4, 2×10−3, 1.7×10−3, respectively. It is quite clear that the Stokes V / I , Q / I and U / I improved a lot after the correction of the polarization offset. The main disadvantage of the method is that it can only correct the crosstalk from Stokes I to Q , U and V , incapable of the correction of that from Stokes V to Q and U . Some other methods are needed so as to make up the disadvantages. We suggest that the above mentioned method can be considered as one of the calibration methods for the space-borne or remote unattended full-disk solar observing instrument because it only uses the routine observation data without any other special calibration observation.