Steps Toward a Large-Scale Solar Image Data Analysis to Differentiate Solar Phenomena

We detail the investigation of the first application of several dissimilarity measures for large-scale solar image data analysis. Using a solar-domain-specific benchmark dataset that contains multiple types of phenomena, we analyzed combinations of image parameters with different dissimilarity measures to determine the combinations that will allow us to differentiate between the multiple solar phenomena from both intra-class and inter-class perspectives, where by class we refer to the same types of solar phenomena. We also investigate the problem of reducing data dimensionality by applying multi-dimensional scaling to the dissimilarity matrices that we produced using the previously mentioned combinations. As an early investigation into dimensionality reduction, we investigate by applying multidimensional scaling (MDS) how many MDS components are needed to maintain a good representation of our data (in a new artificial data space) and how many can be discarded to enhance our querying performance. Finally, we present a comparative analysis of several classifiers to determine the quality of the dimensionality reduction achieved with this combination of image parameters, similarity measures, and MDS.     

Turbulence In The Solar Atmosphere: Manifestations And Diagnostics Via Solar Image Processing

Intermittent magnetohydrodynamical turbulence is most likely at work in the magnetized solar atmosphere. As a result, an array of scaling and multi-scaling image-processing techniques can be used to measure the expected self-organization of solar magnetic fields. While these techniques advance our understanding of the physical system at work, it is unclear whether they can be used to predict solar eruptions, thus obtaining a practical significance for space weather. We address part of this problem by focusing on solar active regions and by investigating the usefulness of scaling and multi-scaling image-processing techniques in solar flare prediction. Since solar flares exhibit spatial and temporal intermittency, we suggest that they are the products of instabilities subject to a critical threshold in a turbulent magnetic configuration. The identification of this threshold in scaling and multi-scaling spectra would then contribute meaningfully to the prediction of solar flares. We find that the fractal dimension of solar magnetic fields and their multi-fractal spectrum of generalized correlation dimensions do not have significant predictive ability. The respective multi-fractal structure functions and their inertial-range scaling exponents, however, probably provide some statistical distinguishing features between flaring and non-flaring active regions. More importantly, the temporal evolution of the above scaling exponents in flaring active regions probably shows a distinct behavior starting a few hours prior to a flare and therefore this temporal behavior may be practically useful in flare prediction. The results of this study need to be validated by more comprehensive works over a large number of solar active regions. Sufficient statistics may also establish critical thresholds in the values of the multi-fractal structure functions and/or their scaling exponents above which a flare may be predicted with a high level of confidence. Based on the author's contributed talk “Manifestations and Diagnostics of Turbulence in the Solar Atmosphere”, presented at the Solar Image Processing Workshop II, Annapolis, Maryland, USA, 3–5 November 2004.     

空间太阳望远镜中1-bit图像相关器的实现

两维图像相关跟踪是空间太阳望远镜(SST)主光学望远镜系统达到0.1″分辨率的关键之一。本文提出了采用1-bit相关算法来实现图像快速相关运算,并设计出了基于FPGA DSP架构的相关器硬件结构。25MHz下32×32点图像相关运算在XCV800芯片上实现仅需0.33ms,而硬件规模仅为基于FFT相关器(12-bit数据)的1/9。     

Multichannel Blind Deconvolution As A Tool For Solar Image Restoration

A principle of restoration methods based on multichannel blind deconvolution (MBD) is introduced. The methods assume that for every un-degraded unobservable image several degraded observed images are available. It is better conditioned than classical single channel approach. The first algorithm represents a generalization of iterative deconvolution scheme introduced for single images. The second MBD algorithm is based on so-called subspace technique. The subspace method is not iterative and this possibly implies an implementation that can be computationally more efficient. Both methods are presented in applications to artificial image data (computer-generated multichannel degraded data) with known ideal image to get a comparison with restored one. Performance in a real situation on solar photosphere images is shown.     

A Multifrequency Study of Five Large Radio Galaxies

We present the results of GMRT and VLA observations of five large radio sources over a wide frequency range to investigate their structural and spectral asymmetries. The hot-spot brightness ratios suggest intrinsic source asymmetries, while the spectral indices show evidence of re-acceleration of particles.     

Multi-Scale Gaussian Normalization for Solar Image Processing

Extreme ultra-violet images of the corona contain information over a wide range of spatial scales, and different structures such as active regions, quiet Sun, and filament channels contain information at very different brightness regimes. Processing of these images is important to reveal information, often hidden within the data, without introducing artefacts or bias. It is also important that any process be computationally efficient, particularly given the fine spatial and temporal resolution of Atmospheric Imaging Assembly on the Solar Dynamics Observatory (AIA/SDO), and consideration of future higher resolution observations. A very efficient process is described here, which is based on localised normalising of the data at many different spatial scales. The method reveals information at the finest scales whilst maintaining enough of the larger-scale information to provide context. It also intrinsically flattens noisy regions and can reveal structure in off-limb regions out to the edge of the field of view. We also applied the method successfully to a white-light coronagraph observation.     

Solar Total Irradiance: A Reference Value for Solar Minimum

Simultaneous solar total irradiance observations performed by absolute radiometers on board satellites during the quiet-Sun period between solar cycles 21 and 22 (1985–1987), are analyzed to determine the solar total irradiance at 1 AU for the solar minimum. During the quiet-Sun period the total solar irradiance, UV irradiance, and the various solar activity indices show very little fluctuation. However, the absolute value of the solar total irradiance derived from the observations differ within the accuracy of the radiometers used in the measurements. Therefore, the question often arises about a reference value of the solar total irradiance for use in climate models and for computation of geophysical, and atmospheric parameters. This research is conducted as a part of the Solar Electromagnetic Radiation Study for Solar Cycle 22 (SOLERS22). On the basis of the study we recommended a reference value of 1367.0 ± 0.04 W m^-2 for the solar total irradiance at 1 AU for a truly quiet Sun. We also find that the total solar irradiance data for the quiet-Sun period reveals strong short-term irradiance variations.     

Review of Image Quality Measures for Solar Imaging

Observations of the solar photosphere from the ground encounter significant problems caused by Earth’s turbulent atmosphere. Before image reconstruction techniques can be applied, the frames obtained in the most favorable atmospheric conditions (the so-called lucky frames) have to be carefully selected. However, estimating the quality of images containing complex photospheric structures is not a trivial task, and the standard routines applied in nighttime lucky imaging observations are not applicable. In this paper we evaluate 36 methods dedicated to the assessment of image quality, which were presented in the literature over the past 40 years. We compare their effectiveness on simulated solar observations of both active regions and granulation patches, using reference data obtained by the Solar Optical Telescope on the Hinode satellite. To create images that are affected by a known degree of atmospheric degradation, we employed the random wave vector method, which faithfully models all the seeing characteristics. The results provide useful information about the method performances, depending on the average seeing conditions expressed by the ratio of the telescope’s aperture to the Fried parameter, \(D/r_{0}\). The comparison identifies three methods for consideration by observers: Helmli and Scherer’s mean, the median filter gradient similarity, and the discrete cosine transform energy ratio. While the first method requires less computational effort and can be used effectively in virtually any atmospheric conditions, the second method shows its superiority at good seeing (\(D/r_{0}<4\)). The third method should mainly be considered for the post-processing of strongly blurred images.     

JPEG2000 Image Compression on Solar EUV Images

For future solar missions as well as ground-based telescopes, efficient ways to return and process data have become increasingly important. Solar Orbiter, which is the next ESA/NASA mission to explore the Sun and the heliosphere, is a deep-space mission, which implies a limited telemetry rate that makes efficient onboard data compression a necessity to achieve the mission science goals. Missions like the Solar Dynamics Observatory (SDO) and future ground-based telescopes such as the Daniel K. Inouye Solar Telescope, on the other hand, face the challenge of making petabyte-sized solar data archives accessible to the solar community. New image compression standards address these challenges by implementing efficient and flexible compression algorithms that can be tailored to user requirements. We analyse solar images from the Atmospheric Imaging Assembly (AIA) instrument onboard SDO to study the effect of lossy JPEG2000 (from the Joint Photographic Experts Group 2000) image compression at different bitrates. To assess the quality of compressed images, we use the mean structural similarity (MSSIM) index as well as the widely used peak signal-to-noise ratio (PSNR) as metrics and compare the two in the context of solar EUV images. In addition, we perform tests to validate the scientific use of the lossily compressed images by analysing examples of an on-disc and off-limb coronal-loop oscillation time-series observed by AIA/SDO.     

Automatic Solar Filament Detection Using Image Processing Techniques

We present an automatic solar filament detection algorithm based on image enhancement, segmentation, pattern recognition, and mathematical morphology methods. This algorithm cannot only detect filaments, but can also identify spines, footpoints, and filament disappearances. It consists of five steps: (1) The stabilized inverse diffusion equation (SIDE) is used to enhance and sharpen filament contours. (2) A new method for automatic threshold selection is proposed to extract filaments from local background. (3) The support vector machine (SVM) is used to differentiate between sunspots and filaments. (4) Once a filament is identified, morphological thinning, pruning, and adaptive edge linking methods are used to determine the filament properties. (5) Finally, we propose a filament matching method to detect filament disappearances. We have successfully applied the algorithm to Hα full-disk images obtained at Big Bear Solar Observatory (BBSO). It has the potential to become the foundation of an automatic solar filament detection system, which will enhance our capabilities of forecasting and predicting geo-effective events and space weather.     

Image Quality in High-resolution and High-cadence Solar Imaging

Broad-band imaging and even imaging with a moderate bandpass (about 1 nm) provides a photon-rich environment, where frame selection (lucky imaging) becomes a helpful tool in image restoration, allowing us to perform a cost-benefit analysis on how to design observing sequences for imaging with high spatial resolution in combination with real-time correction provided by an adaptive optics (AO) system. This study presents high-cadence (160 Hz) G-band and blue continuum image sequences obtained with the High-resolution Fast Imager (HiFI) at the 1.5-meter GREGOR solar telescope, where the speckle-masking technique is used to restore images with nearly diffraction-limited resolution. The HiFI employs two synchronized large-format and high-cadence sCMOS detectors. The median filter gradient similarity (MFGS) image-quality metric is applied, among others, to AO-corrected image sequences of a pore and a small sunspot observed on 2017 June 4 and 5. A small region of interest, which was selected for fast-imaging performance, covered these contrast-rich features and their neighborhood, which were part of Active Region NOAA 12661. Modifications of the MFGS algorithm uncover the field- and structure-dependency of this image-quality metric. However, MFGS still remains a good choice for determining image quality without a priori knowledge, which is an important characteristic when classifying the huge number of high-resolution images contained in data archives. In addition, this investigation demonstrates that a fast cadence and millisecond exposure times are still insufficient to reach the coherence time of daytime seeing. Nonetheless, the analysis shows that data acquisition rates exceeding 50 Hz are required to capture a substantial fraction of the best seeing moments, significantly boosting the performance of post-facto image restoration.     

Analysis and Packaging of Radiochemical Solar Neutrino Data: A Bayesian Approach

According to current practice, the results of each run of a radiochemical solar neutrino experiment comprise an estimate of the flux and upper and lower error estimates. These estimates are derived by a maximum-likelihood procedure from the times of decay events in the analysis chamber. This procedure has the following shortcomings: (a) published results sometimes include negative flux estimates; (b) even if the flux estimate is non-negative, the probability distribution function implied by the flux and error estimates will extend into negative territory; and (c) the overall flux estimate derived from the results of a sequence of runs may differ substantially from an estimate made by a “global” analysis of all of the timing data taken together. These defects indicate that the usual “packaging” of data in radiochemical solar neutrino experiments provides an inadequate summary of the data, which implies a loss of information. This article reviews this problem from a Bayesian perspective, and we suggest an alternative scheme for the packaging of radiochemical solar neutrino data, which we believe is free from these shortcomings.     

Precise Determination of the Orientation of the Solar Image

Accurate heliographic coordinates of objects on the Sun have to be known in several fields of solar physics. One of the factors that affect the accuracy of the measurements of the heliographic coordinates is the accuracy of the orientation of a solar image. In this paper the well-known drift method for determining the orientation of the solar image is applied to data taken with a solar telescope equipped with a CCD camera. The factors that influence the accuracy of the method are systematically discussed, and the necessary corrections are determined. These factors are as follows: the trajectory of the center of the solar disk on the CCD with the telescope drive turned off, the astronomical refraction, the change of the declination of the Sun, and the optical distortion of the telescope. The method can be used on any solar telescope that is equipped with a CCD camera and is capable of taking solar full-disk images. As an example to illustrate the method and its application, the orientation of solar images taken with the Gyula heliograph is determined. As a byproduct, a new method to determine the optical distortion of a solar telescope is proposed.     

Estimation Of Seeing Quality Using Low-Resolution Solar Image Data

Modulation transfer functions (MTFs), generated as a by-product of the analysis of low-resolution solar images taken for the Global Oscillation Network Group, were used to estimate the quality of seeing at its six sites. These MTFs, after approximate correction for the effects of the instrumental point spread function, were fitted with physically-motived functional forms representing the effects of seeing and scattering. It was found that the estimates of seeing quality were relatively robust to the effects of scattering, but were severely biased by effects caused by changes in instrumental focus. Relative trends in seeing quality are preserved on time scales shorter than a few months and it is found that local topography dominates the observed trends in daytime seeing quality.     

Statistical Study of Short Quiescent Times between Solar Flares in a 1D MHD Model

The statistical distribution of short quiescent times 30 min) between solar flares has been investigated with a 1D MHD model. A power-law behaviour is found which indicates the existence of sympathetic flaring. This prediction is supported by recent observations.     

1-2GHz太阳射电动态频谱仪

本文描述了北京天文台研制的１－２ＧＨｚ太阳射电动态频谱仪的性能、结构、初步观测结果及进一步改进计划．     

3D Solar Null Point Reconnection MHD Simulations

Numerical MHD simulations of 3D reconnection events in the solar corona have improved enormously over the last few years, not only in resolution, but also in their complexity, enabling more and more realistic modeling. Various ways to obtain the initial magnetic field, different forms of solar atmospheric models as well as diverse driving speeds and patterns have been employed. This study considers differences between simulations with stratified and non-stratified solar atmospheres, addresses the influence of the driving speed on the plasma flow and energetics, and provides quantitative formulas for mapping electric fields and dissipation levels obtained in numerical simulations to the corresponding solar quantities. The simulations start out from a potential magnetic field containing a null-point, obtained from a Solar and Heliospheric Observatory (SOHO) Michelson Doppler Imager (MDI) magnetogram magnetogram extrapolation approximately 8?hours before a C-class flare was observed. The magnetic field is stressed with a boundary motion pattern similar to?–?although simpler than?–?horizontal motions observed by SOHO during the period preceding the flare. The general behavior is nearly independent of the driving speed, and is also very similar in stratified and non-stratified models, provided only that the boundary motions are slow enough. The boundary motions cause a build-up of current sheets, mainly in the fan-plane of the magnetic null-point, but do not result in a flare-like energy release. The additional free energy required for the flare could have been partly present in non-potential form at the initial state, with subsequent additions from magnetic flux emergence or from components of the boundary motion that were not represented by the idealized driving pattern.     

Stokes Diagnostics of 2D MHD-Simulated Solar Magnetogranulation

The properties of solar magnetic fields on scales less than the spatial resolution of solar telescopes are studied. A synthetic infrared spectropolarimetric diagnostic based on a 2D MHD simulation of magnetoconvection is used for this. Analyzed are two time sequences of snapshots that likely represent two regions of the network fields with their immediate surroundings on the solar surface with unsigned magnetic flux densities of 300 and 140 G. In the first region from the probability density functions of the magnetic field strength it is found that the most probable field strength at log τ ₅=0 is equal to 250 G. Weak fields (B<500 G) occupy about 70% of the surface, whereas stronger fields (B>1000 G) occupy only 9.7% of the surface. The magnetic flux is −28 G and its imbalance is −0.04. In the second region, these parameters are correspondingly equal to 150 G, 93.3%, 0.3%, −40 G, and −0.10. The distribution of line-of-sight velocities on the surface of log τ ₅=−1 is estimated. The mean velocity is equal to 0.4 km s⁻¹ in the first simulated region. The average velocity in the granules is −1.2 km s⁻¹ and in the intergranules it is 2.5 km s⁻¹. In the second region, the corresponding values of the mean velocities are equal to 0, −1.8, and 1.5 km s⁻¹. In addition the asymmetry of synthetic Stokes V profiles of the Fe i 1564.8 nm line is analyzed. The mean values of the amplitude and area asymmetry do not exceed 1%. The spatially smoothed amplitude asymmetry is increased to 10% whereas the area asymmetry is only slightly varied.     

CMOS图像传感器在太阳磁场观测中的应用研究

磁场是太阳物理的第1观测量,当前太阳磁场观测研究正迈向大视场、高时空分辨率、高偏振测量精度以及空间观测的时代.中国首颗太阳观测卫星—先进天基太阳天文台(ASO-S)也配置了具有高时空分辨率、高磁场灵敏度的全日面矢量磁像仪(FMG)载荷,针对FMG载荷的需求,讨论了大面阵、高帧频互补金属氧化物半导体(Complementary Metal Oxide Semiconductor, CMOS)图像传感器应用于太阳磁场观测的可行性.首先,基于滤光器型太阳磁像仪观测的原理,比较分析了目前CMOS图像传感器(可用的或是可选的两种快门模式)的特点,指出全局快门类型更适合FMG;其次搭建了CMOS传感器实验室测试系统,测量了CMOS图像传感器的像素增益及其分布规律;最后在怀柔太阳观测基地的全日面太阳望远镜上开展了实测验证,获得预期成果.在这些研究基础上,形成了FMG载荷探测器选型方向.