Automatic Detection of Magnetic δ in Sunspot Groups

Large and magnetically complex sunspot groups are known to be associated with flares. To date, the Mount Wilson scheme has been used to classify sunspot groups based on their morphological and magnetic properties. The most flare-prolific class, the δ sunspot group, is characterised by opposite-polarity umbrae within a common penumbra, separated by less than 2∘. In this article, we present a new system, called the Solar Monitor Active Region Tracker-Delta Finder (SMART-DF), which can be used to automatically detect and classify magnetic δ s in near-realtime. Using continuum images and magnetograms from the Helioseismic and Magnetic Imager (HMI) onboard NASA’s Solar Dynamics Observatory (SDO), we first estimate distances between opposite-polarity umbrae. Opposite-polarity pairs with distances of less that 2∘ are then identified, and if these pairs are found to share a common penumbra, they are identified as a magnetic δ configuration. The algorithm was compared to manual δ detections reported by the Space Weather Prediction Center (SWPC), operated by the National Oceanic and Atmospheric Administration (NOAA). SMART-DF detected 21 out of 23 active regions (ARs) that were marked as δ spots by NOAA during 2011 – 2012 (within ±60∘ longitude). SMART-DF in addition detected five ARs that were not announced as δ spots by NOAA. The near-realtime operation of SMART-DF resulted in many δ s being identified in advance of NOAA’s daily notification. SMART-DF will be integrated into SolarMonitor ( www.solarmonitor.org ) and the near-realtime information will be available to the public

Representation of solar features in 3D for creating visual solar catalogues

YesIn this study a method for 3D representation of active regions and sunspots that are detected from Solar and Heliospheric Observatory/Michelson Doppler Imager magnetogram and continuum images is provided. This is our first attempt to create a visual solar catalogue. Because of the difficulty of providing a full description of data in text based catalogues, it can be more accurate and effective for scientist to search 3D solar feature models and descriptions at the same time in such a visual solar catalogue. This catalogue would improve interpretation of solar images, since it would allow us to extract data embedded in various solar images and visualize it at the same time. In this work, active regions that are detected from magnetogram images and sunspots that are detected from continuum images are represented in 3D coordinates. Also their properties extracted from text based catalogues are represented at the same time in 3D environment. This is the first step for creating a 3D solar feature catalogue where automatically detected solar features will be presented visually together with their properties

Automated recognition of sunspots on the SOHO/MDI white light solar images

A new technique is presented for automatic identification of sunspots on the full disk solar images allowing robust detection of sunspots on images obtained from space and ground observations, which may be distorted by weather conditions and instrumental artefacts. The technique applies image cleaning procedures for elimination of limb darkening, intensity noise and noncircular image shape. Sobel edge-detection is applied to find sunspot candidates. Morphological operations are then used to filter out noise and define a local neighbourhood background via thresholding, with threshold levels defined as a function of the quiet sun intensity and local statistical properties. The technique was tested on one year (2002) of full disk SOHO/MDI white light (WL) images. The detection results are in very good agreement with the Mendon manual synoptic maps as well as with the Locarno Observatory Sunspot manual drawings. The detection results from WL observations are cross-referenced with the SOHO/MDI magnetogram data for verification purposes

Automated system design for the efficient processing of solar satellite images. Developing novel techniques and software platform for the robust feature detection and the creation of 3D anaglyphs and super-resolution images for solar satellite images.

The Sun is of fundamental importance to life on earth and is studied by scientists from many disciplines. It exhibits phenomena on a wide range of observable scales, timescales and wavelengths and due to technological developments there is a continuing increase in the rate at which solar data is becoming available for study which presents both opportunities and challenges. Two satellites recently launched to observe the sun are STEREO (Solar TErrestrial RElations Observatory), providing simultaneous views of the SUN from two different viewpoints and SDO (Solar Dynamics Observatory) which aims to study the solar atmosphere on small scales and times and in many wavelengths. The STEREO and SDO missions are providing huge volumes of data at rates of about 15 GB per day (initially it was 30 GB per day) and 1.5 terabytes per day respectively. Accessing these huge data volumes efficiently at both high spatial and high time resolutions is important to support scientific discovery but requires increasingly efficient tools to browse, locate and process specific data sets. This thesis investigates the development of new technologies for processing information contained in multiple and overlapping images of the same scene to produce images of improved quality. This area in general is titled Super Resolution (SR), and offers a technique for reducing artefacts and increasing the spatial resolution. Another challenge is to generate 3D images such as Anaglyphs from uncalibrated pairs of SR images. An automated method to generate SR images is presented here. The SR technique consists of three stages: image registration, interpolation and filtration. Then a method to produce enhanced, near real-time, 3D solar images from uncalibrated pairs of images is introduced. Image registration is an essential enabling step in SR and Anaglyph processing. An accurate point-to-point mapping between views is estimated, with multiple images registered using only information contained within the images themselves. The performances of the proposed methods are evaluated using benchmark evaluation techniques. A software application called the SOLARSTUDIO has been developed to integrate and run all the methods introduced in this thesis. SOLARSTUDIO offers a number of useful image processing tools associated with activities highly focused on solar images including: Active Region (AR) segmentation, anaglyph creation, solar limb extraction, solar events tracking and video creation