BRADFORD SCHOLARS

    • Sign in
    View Item 
    •   Bradford Scholars
    • University of Bradford eTheses
    • Theses
    • View Item
    •   Bradford Scholars
    • University of Bradford eTheses
    • Theses
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of Bradford ScholarsCommunitiesAuthorsTitlesSubjectsPublication DateThis CollectionAuthorsTitlesSubjectsPublication Date

    My Account

    Sign in

    HELP

    Bradford Scholars FAQsCopyright Fact SheetPolicies Fact SheetDeposit Terms and ConditionsDigital Preservation Policy

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Development of digital imaging technologies for the segmentation of solar features and the extraction of filling factors from SODISM images

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Thumbnail
    View/Open
    PhD Thesis (7.897Mb)
    Download
    Publication date
    2018
    Author
    Alasta, Amro F.A.
    Supervisor
    Qahwaji, Rami S.R.
    Ipson, Stanley S.
    Keyword
    Solar Diameter Imager And Surface Mapper (SODISM)
    Solar imaging
    Sunspots
    Digital imaging
    Segmentation
    Resolution enhancement
    Discrete wavelet transforms
    Solar filling factor
    Rights
    Creative Commons License
    The University of Bradford theses are licenced under a Creative Commons Licence.
    Institution
    University of Bradford
    Department
    School of Electrical Engineering and computer. Science Faculty of Engineering and Informatics
    Awarded
    2018
    
    Metadata
    Show full item record
    Abstract
    Solar images are one of the most important sources of available information on the current state and behaviour of the sun, and the PICARD satellite is one of several ground and space-based observatories dedicated to the collection of that data. The PICARD satellite hosts the Solar Diameter Imager and Surface Mapper (SODISM), a telescope aimed at continuously monitoring the Sun. It has generated a huge cache of images and other data that can be analysed and interpreted to improve the monitoring of features, such as sunspots and the prediction and diagnosis of solar activity. In proportion to the available raw material, the little-published analysis of SODISM data has provided the impetus for this study, specifically a novel method of contributing to the development of a system to enhance, detect and segment sunspots using new hybrid methods. This research aims to yield an improved understanding of SODISM data by providing novel methods to tabulate a sunspot and filling factor (FF) catalogue, which will be useful for future forecasting activities. The developed technologies and the findings achieved in this research will work as a corner stone to enhance the accuracy of sunspot segmentation; create efficient filling factor catalogue systems, and enhance our understanding of SODISM image enhancement. The results achieved can be summarised as follows: i) Novel enhancement method for SODISM images. ii) New efficient methods to segment dark regions and detect sunspots. iii) Novel catalogue for filling factor including the number, size and sunspot location. v) Novel statistical method to summarise FFs catalogue. Image processing and partitioning techniques are used in this work; these methods have been applied to remove noise and detect sunspots and will provide more information such as sunspot numbers, size and filling factor. The performance of the model is compared to the fillers extracted from other satellites, such as SOHO. Also, the results were compared with the NOAA catalogue and achieved a precision of 98%. Performance measurement is also introduced and applied to verify results and evaluate proposal methods. Algorithms, implementation, results and future work have been explained in this thesis.
    URI
    http://hdl.handle.net/10454/18663
    Type
    Thesis
    Qualification name
    PhD
    Collections
    Theses

    entitlement

     
    DSpace software (copyright © 2002 - 2022)  DuraSpace
    Quick Guide | Contact Us
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.