Development of an Automatic Filament Disappearance Detection System

This paper presents an efficient and automatic method for detecting filament disappearances. This method was applied to the Big Bear Solar Observatory's (BBSO) full-disk H images. The initial step is to detect the filaments in the solar image, then determine if they are growing, stable or disappearing. If a disappearing filament is found, the solar community can be automatically alerted in near real time. This system is proven to be accurate and fast. In addition, three statistical studies of the appearance and disappearance of all filaments in 1999 are presented.     

Developing an Advanced Automated Method for Solar Filament Recognition and Its Scientific Application to a Solar Cycle of MLSO Hα Data

We developed a method to automatically detect and trace solar filaments in Hα full-disk images. The program is able not only to recognize filaments and determine their properties, such as the position, the area, the spine, and other relevant parameters, but also to trace the daily evolution of the filaments. The program consists of three steps: First, preprocessing is applied to correct the original images; second, the Canny edge-detection method is used to detect filaments; third, filament properties are recognized through morphological operators. To test the algorithm, we successfully applied it to observations from the Mauna Loa Solar Observatory (MLSO). We analyzed Hα images obtained by the MLSO from 1998 to 2009 and obtained a butterfly diagram of filaments. This shows that the latitudinal migration of solar filaments has three trends in Solar Cycle 23: The drift velocity was fast from 1998 to the solar maximum, after which it became relatively slow. After 2006, the migration became divergent, signifying the solar minimum. About 60 % of the filaments with latitudes higher than 50^° migrate toward the polar regions with relatively high velocities, and the latitudinal migrating speeds in the northern and the southern hemispheres do not differ significantly in Solar Cycle 23.     

基于支持向量机的太阳磁场活动区极性反转线位置的探测

太阳磁场的极性反转线(Polarity Inversion Line, PIL)是研究太阳活动、分析太阳磁场结构演变和预测太阳耀斑最重要的日面特征之一.磁场极性反转的位置是太阳耀斑和暗条可能出现的位置."先进天基太阳天文台(ASO-S)"是中国首颗空间太阳专用观测卫星,其搭载的"全日面矢量磁像仪(Full-Disk Vector Magnetograph, FMG)"主要任务是探测高空间、高时间分辨率的全日面矢量磁场.为了提高观测数据使用效率、快速监测太阳活动水平、提高太阳耀斑与日冕物质抛射的预报水平以及更好地服务于FMG数据处理与分析系统,采用了图像自动识别与处理技术,更加精确有效地检测极性反转线.从支持向量机(Support Vector Machine, SVM)的模型出发,将极性反转线位置的探测问题转化为一个模式识别中的二分类问题,提出了一种基于支持向量机的极性反转线检测算法,自动探测与识别太阳动力学天文台(Solar Dynamics Observatory, SDO)日震和磁成像仪(Helioseismic and Magnetic Imager, HMI)磁图的极性反转线位置.与现有算法的对比结果表明,此算法可以精确直观地检测太阳活动区的极性反转线.     

A Comparative Evaluation of Automated Solar Filament Detection

We present a comparative evaluation for automated filament detection in Hα solar images. By using metadata produced by the Advanced Automated Filament Detection and Characterization Code (AAFDCC) module, we adapted our trainable feature recognition (TFR) module to accurately detect regions in solar images containing filaments. We first analyze the AAFDCC module’s metadata and then transform it into labeled datasets for machine-learning classification. Visualizations of data transformations and classification results are presented and accompanied by statistical findings. Our results confirm the reliable event reporting of the AAFDCC module and establishes our TFR module’s ability to effectively detect solar filaments in Hα solar images.     

Automated Detection of Filaments and Their Disappearance Using Full-Disc Hα Images

A new algorithm is presented that automatically detects filaments on the Sun in full-disc Hα images. Pre-processing of Hα images includes corrections for limb darkening and foreshortening. Further, by applying suitable intensity and size thresholds, filaments are extracted, while other solar features, e.g. sunspots and plages, are removed. Filament attributes such as their position on the solar disc, total area, length, and number of fragments are determined. In addition, every filament is also labelled with a unique number for identification. The algorithm is capable of following a particular filament through successive images, which allows us to detect their changes and disappearance. We have analysed ten cases of filament eruption from different observatories, and the results obtained are presented. The algorithm will eventually be integrated with an upcoming telescope at the Udaipur Solar Observatory for real-time monitoring of activated/eruptive filaments. This aspect should prove to be of particular importance in studies pertaining to space weather.     

Automatic Solar Filament Segmentation and Characterization

This paper presents a generic method to automatically segment and characterize solar filaments from various Hα full-disk solar images, obtained by different solar observatories, with different dynamic ranges and statistical properties. First, a cascading Hough circle detector is designed to find the center location and radius of the solar disks. Second, polynomial surface fitting is adopted to correct unbalanced luminance. Third, an adaptive thresholding method is put forward to segment solar filaments. Finally, for each piece of a solar filament, its centroid location, area, and length are characterized, in which morphological thinning and graph theory are used for identifying the main skeletons of filaments. To test the performance of the proposed methods, a dataset composed of 125 Hα images is considered. These images were obtained by four solar observatories from January 2000 to May 2010, one image per month. Experimental results show that the accuracy rate is above 95% as measured by filament number and above 99% as measured by filament area, indicating that only a few tiny filaments are not detected.     

Automated Technique For Comparison Of Magnetic Field Inversion Lines With Filament Skeletons From The Solar Feature Catalogue

We present an automated technique for comparison of magnetic field inversion-line maps from SOHO/MDI magnetograms with solar filament data from the Solar Feature Catalogue created as part of the European Grid of Solar Observations project. The Euclidean distance transform and connected component labelling are used to identify nearest inversion lines to filament skeletons. Several filament inversion-line characteristics are defined and used to automate the decision whether a particular filament/inversion-line pair is suitable for quantitative comparison of orientation and separation. The technique is tested on 551 filaments from 14 Hα images at various dates, and the distributions of angles and distances between filament skeletons and line-of-sight (LOS) magnetic inversion lines are presented for six levels of magnetic field smoothing. The results showed the robustness of the developed technique which can be applied for a statistical analysis of magnetic field in the vicinity of filaments. The method accuracy is limited by the static filament detection which does not distinguish between filaments, fibrils, pre-condensations and filament barbs and this may increase the asymmetries in magnetic distributions and broadening in angular distributions that requires the incorporation of a feature tracking technique.     

A Method of Resolving the 180-Degree Ambiguity by Employing the Chirality of Solar Features

The 180-degree ambiguity in magnetic field direction along polarity reversal boundaries can be resolved often and reliably by the chiral method. The chiral method requires (1) identification of the chirality of at least one solar feature related to a polarity reversal boundary along which the field direction is sought and (2) knowledge of the polarity of the network magnetic field on at least one side of the polarity reversal boundary. In the context of the Sun, chirality is an observable signature of the handedness of the magnetic field of a solar feature. We concentrate on how to determine magnetic field direction from chirality definitions and illustrate the technique in eight examples. The examples cover the spectrum of polarity boundaries associated with filament channels and filaments ranging from those connected with active regions to those on the quiet Sun. The applicability of the chiral method to all categories of filaments supports the view that active region filaments and quiescent filaments are the extreme ends in a continuous spectrum of filaments. The chiral method is almost universally applicable because many types of solar features that reveal chirality are now readily seen in solar images accessible over the World Wide Web; also there are clear differences between left-handed and right-handed solar structures that can be identified in both high- and low-resolution data although high-resolution images are almost always preferable. In addition to filaments and filament channels, chirality is identifiable in coronal loop systems, flare loop systems, sigmoids, some sunspots, and some erupting prominences. Features other than filament channels and filaments can be used to resolve the 180-degree ambiguity because there is a one-to-one relationship between the chiralities of all features associated with a given polarity reversal boundary. Y. Lin is now at the Institute of Theoretical Astrophysics, University of Oslo.     

The relationships between disappearing solar filaments,coronal mass ejections,and geomagnetic activity

The relationships between disappearing solar filaments and geomagnetic activity are examined using data obtained between 1974 and 1980. The average level of geomagnetic activity is found to increase after the disappearance of large filaments. The magnitudes of the geomagnetic disturbances depend upon the sizes and, to a lesser extent, upon the darkness of the filaments. The delays between filament disappearances and resulting geomagnetic disturbances are typically 3–6 days, corresponding to Sun-Earth velocities 580–290 km s^–1. These are consistent with the observed velocities of those coronal mass ejections that are associated with disappearing filaments.The average delay is: (a) shorter for large and dark filaments than for small and faint filaments respectively; (b) shorter during solar maximum than during solar minimum; (c) dependent in a complex way upon the longitudes of the filaments. Disturbances associated with filaments with longitudes 50 ° have delays 10 days.Quieter than average geomagnetic conditions sometimes occur for several days prior to the geomagnetic disturbances that follow disappearing filaments.     

基于改进VNet太阳暗条检测方法

太阳暗条作为太阳大气磁场的示踪,对研究太阳磁场有极其重要的意义。针对现有的暗条检测方法存在检测精度不高,弱小暗条错检、漏检等问题,提出一种基于改进VNet网络的太阳暗条检测方法。首先,使用大熊湖天文台Hα全日面图像并结合磁图制作了太阳暗条数据集;其次,在VNet网络下采样部分采用Inception模块融合不同尺度特征图的特征,同时加入注意力机制增强特征图中暗条部分的语义信息;最后在上采样部分引入深度监督模块,更多地保留太阳暗条的细节特征。为验证算法性能,采用191幅Hα全日面图像数据集,其中包含暗条共3372条。算法在测试数据集上平均准确率达到0.9883,F1值达到0.8385。实验结果证明,该方法可以有效识别Hα全日面图中的暗条。     

Filament Recognition In Solar Images With The Neural Network Technique

We describe a new technique developed for an automated recognition of solar filaments visible in Hα hydrogen line full-disk spectroheliograms. These filaments are difficult to recognize because of variability in the background caused by atmospheric conditions. The presented technique is based on an artificial neural network (ANN) consisting of two hidden neurons and one output neuron which learn to exclude the contribution of a changeable background to a filament. The ANN is trained on a single image fragment labeled manually to recognize the filament elements depicted on a local background. The background contribution is approximated with linear and parabolic functions. This technique applied to the filament recognition in 54 cropped images reveals better detection results for a parabolic approximation than for a linear one approaching an accuracy of about 82% of the total filament pixels.     

Dynamic and Thermal Disappearance of Prominences and Their Geoeffectiveness

This paper is a qualitative study of 42 events of solar filament/prominence sudden disappearances (“disparitions brusques”; henceforth DBs) around two solar minima, 1985 – 1986 and 1994. The studied events were classified as 17 thermal and 25 dynamic disappearances. Associated events, i.e. coronal mass ejections (CMEs), type II bursts, evolution of nearby coronal holes, as well as solar wind speed, and geomagnetic disturbances are discussed. We have found that about 50% of the thermal DBs with adjacent (within 15° from the DB) coronal holes were associated with CMEs within a selected time window. All the studied thermal disappearances with adjacent coronal holes or accompanied by dynamic disappearances were associated with weak and medium geomagnetic storms. Also, nearly 64% of dynamic DBs were associated with CMEs. Ten (40%) dynamic disappearances were associated with intense geomagnetic storms, even when no CMEs was reported, six (24%) dynamic disappearances corresponded to extreme storms, and five (20%) corresponded to medium geomagnetic storms. The extreme geomagnetic storms appeared to be related to combined events, involving dynamic disappearances with adjacent coronal holes or including thermal disappearances. Furthermore, the geomagnetic activity (Dst index) increased if the source was close to the central meridian (±30°). The highest interplanetary magnetic field (B), longest duration, lowest southward direction B _z component, and lowest Dst were highly correlated for all studied events. The Sun – Earth transit time computed from the starting time of the sudden disappearance and the time its effect was measured at Earth was about 4.3 days and was mainly well correlated with the solar wind speed measured in situ (daily value).     

Properties of filaments in solar cycle 20-23 from McIntosh Archive

A filament is a cool, dense structure suspended in the solar corona. The eruption of a filament is often associated with a coronal mass ejection(CME), which has an adverse effect on space weather. Hence,research on filaments has attracted much attention in the recent past. The tilt angle of active region(AR)magnetic bipoles is a crucial parameter in the context of the solar dynamo, which governs the conversion efficiency of the toroidal magnetic field to poloidal magnetic field. Filaments always form over polarity inversion lines(PILs), so the study of tilt angles for these filaments can provide valuable information about generation of a magnetic field in the Sun. We investigate the tilt angles of filaments and other properties using McIntosh Archive data. We fit a straight line to each filament to estimate its tilt angle. We examine the variation of mean tilt angle with time. The latitude distribution of positive tilt angle filaments and negative tilt angle filaments reveals that there is a dominance of positive tilt angle filaments in the southern hemisphere and negative tilt angle filaments dominate in the northern hemisphere. We study the variation of the mean tilt angle for low and high latitudes separately. Investigations of temporal variation with filament number indicate that total filament number and low latitude filament number vary cyclically, in phase with the solar cycle. There are fewer filaments at high latitudes and they also show a cyclic pattern in temporal variation. We also study the north-south asymmetry of filaments with different latitude criteria.     

A new algorithm for the detection of intercluster galaxy filaments using galaxy orientation alignments

We present a new algorithm for detecting intercluster galaxy filaments based upon the assumption that the orientations of constituent galaxies along such filaments are non-isotropic. We apply the algorithm to the 2dF Galaxy Redshift Survey catalogue and find that it readily detects many straight filaments between close cluster pairs. At large intercluster separations  (≫15  h ⁻¹ Mpc)  , we find that the detection efficiency falls quickly, as it also does with more complex filament morphologies. We explore the underlying assumptions and suggest that it is only in the case of close cluster pairs that we can expect galaxy orientations to be significantly correlated with filament direction.     

Activity cycle of solar filaments

Long-term variation in the distribution of the solar filaments observed at the Observatorie de Paris, Section de Meudon from March 1919 to December 1989 is presented to compare with sunspot cycle and to study the periodicity in the filament activity, namely the periods of the coronal activity with the Morlet wavelet used. It is inferred that the activity cycle of solar filaments should have the same cycle length as sunspot cycle, but the cycle behavior of solar filaments is globally similar in profile with, but different in detail from, that of sunspot cycles. The amplitude of solar magnetic activity should not keep in phase with the complexity of solar magnetic activity. The possible periods in the filament activity are about 10.44 and 19.20 years. The wavelet local power spectrum of the period 10.44 years is statistically significant during the whole consideration time. The wavelet local power spectrum of the period 19.20 years is under the 95% confidence spectrum during the whole consideration time, but over the mean red-noise spectrum of α = 0.72 before approximate Carrington rotation number 1500, and after that the filament activity does not statistically show the period. Wavelet reconstruction indicates that the early data of the filament archive (in and before cycle 16) are more noiseful than the later (in and after cycle 17).     

Automation of the Filament Tracking in the Framework of the HELIO Project

We present a new method to automatically track filaments over the solar disk. The filaments are first detected on Meudon Spectroheliograph Hα images of the Sun, applying the technique developed by Fuller, Aboudarham, and Bentley (Solar Phys. 227, 61, 2005). This technique combines cleaning processes, image segmentation based on region growing, and morphological parameter extraction, including the determination of filament skeletons. The coordinates of the skeleton pixels, given in a heliocentric system, are then converted to a more appropriate reference frame that follows the rotation of the Sun surface. In such a frame, a co-rotating filament is always located around the same position, and its skeletons (extracted from each image) are thus spatially close, forming a group of adjacent features. In a third step, the shape of each skeleton is compared with its neighbours using a curve-matching algorithm. This step will permit us to define the probability [P] that two close filaments in the co-rotating frame are actually the same one observed on two different images. At the end, the pairs of features, for which the corresponding probability is greater than a threshold value, are associated using tracking identification indices. On a representative sample of filaments, the good agreement between automated and manual tracking confirms the reliability of the technique to be applied on large data sets. This code is already used in the framework of the Heliophysics Integrated Observatory (HELIO) to populate a catalogue dedicated to solar and heliospheric features (HFC). An extension of this method to other filament observations, and possibly sunspots, faculae, and coronal-holes tracking, can also be envisaged.     

Dual-filament initiation of a Coronal Mass Ejection: Observations and Model

We propose a new model for the initiation of solar coronal mass ejections (CMEs) and CME-associated flares. The model is inferred from observations of a quiescent filament eruption in the north-western quadrant of the solar disk on 4 September 2000. The event was observed with the Siberian Solar Radio Telescope (5.7 GHz), the Nobeyama Radioheliograph (17 GHz) and SOHO/EIT and LASCO. Based on the observations, we suggest that the eruption could be caused by the interaction of two dextral filaments. According to our model, these two filaments merge together to form a dual-filament system tending to form a single long filament. This results in a slow upward motion of the dual-filament system. Its upward expansion is prevented by the attachment of the filaments to the photosphere by filament barbs as well as by overlying coronal arcades. The initial upward motion is caused by the backbone magnetic field (first driving factor) which connects the two merging filaments. Its magnetic flux increases slowly due to magnetic reconnection of the cross-interacting legs of these filaments. If a total length of the dual-filament system is large enough, then the filament barbs detach themselves from the solar surface due to magnetic reconnection between the barbs with oppositely directed magnetic fields. The detachment of the filament barbs completes the formation of the eruptive filaments themselves and determines the helicity sign of their magnetic fields. The appearance of a helical magnetic structure creates an additional upward-directed force (second driving factor). A combined action of these two factors causes acceleration of the dual-filament system. If the lifting force of the two factors is sufficient to substantially extend the overlying coronal magnetic arcade, then magnetic reconnection starts below the eruptive filament in accordance with the classical scheme, and the third driving factor comes into play.     

ON THE EVOLUTION OF FILAMENTS

A statistical large-scale study of filaments has revealed the existence of a functional dependence of the length of filaments (the angular distance between the ends of a filament, measured on a great circle on a sphere) on their inclination to lines of solar latitude. A cluster analysis method has been applied to the study of filament evolution and an evolutionary classification of filaments is proposed. The results depend on the differential velocity of filaments. Different types of evolution sequences were obtained, and the evolution of some particular filaments was specially analyzed.     

Advanced Automated Solar Filament Detection And Characterization Code: Description, Performance, And Results

We present a code for automated detection, classification, and tracking of solar filaments in full-disk Hα images that can contribute to Living With a Star science investigations and space weather forecasting. The program can reliably identify filaments; determine their chirality and other relevant parameters like filament area, length, and average orientation with respect to the equator. It is also capable of tracking the day-by-day evolution of filaments while they travel across the visible disk. The code was tested by analyzing daily Hα images taken at the Big Bear Solar Observatory from mid-2000 until beginning of 2005. It identified and established the chirality of thousands of filaments without human intervention. We compared the results with a list of filament proprieties manually compiled by Pevtsov, Balasubramaniam and Rogers (2003) over the same period of time. The computer list matches Pevtsov's list with a 72% accuracy. The code results confirm the hemispheric chirality rule stating that dextral filaments predominate in the north and sinistral ones predominate in the south. The main difference between the two lists is that the code finds significantly more filaments without an identifiable chirality. This may be due to a tendency of human operators to be biased, thereby assigning a chirality in less clear cases, while the code is totally unbiased. We also have found evidence that filaments obeying the chirality rule tend to be larger and last longer than the ones that do not follow the hemispherical rule. Filaments adhering to the hemispheric rule also tend to be more tilted toward the equator between latitudes 10^° and 30^°, than the ones that do not.     

On the possible mechanism of formation of emission rim in hydrogen filaments

Hα filtergrams of the chromosphere show an emission rim in many hydrogen filaments. We suppose that formation of this rim is due to photospheric radiation reflected by the filament in the direction of the chromosphere. The calculations show that: (1) the maximum contrast of the rim relative to the undisturbed chromosphere amounts to 1.4; (2) the larger the optical thickness of the filament and the closer to the solar limb it is situated, the brighter and wider is the rim; (3) the rim was not observed in filaments whose heights exceeds 10000km above the chromosphere. These results are in close agreement with observations.