Life on Earth is strongly related to the Sun, which makes it a vital star to
study and understand. To improve our knowledge of the way the Sun works,
many satellites have been launched into space to monitor the Sun‟s activities
where the one of main focus is the effect of these activities on the Earth‟s
climate; PICARD is one such satellite. Due to the noise associated with
SODISM images, the clarity of these images and the appearance of solar
features are affected. Image denoising and enhancement are the main
techniques to improve the visual appearance of SODISM images.
Affective de-noising algorithm methods depend on a proper detecting of
noise present in the image. The aim is to identify which type of noise is
present in the image. To reach this point, supervised machine-learning (ML) classifier is used to classify the type of noise present in the image.
Furthermore, this work introduces a novel technique developed to enhance
the quality of SODISM images. In this thesis, the Modified Undecimated Discrete Wavelet Transform (M-UDWT) technique is used to de-noise and
enhance the quality of SODISM images. The proposed method is robust and
effectively improves the quality of SODISM images, and produces more
precise information and clear feature are brought out. In addition, the non wavelet enhancement is developed as well in this thesis. The results of this
algorithm is discussed. The new methods are also assessed using two
different methods: subjective (by human observation) and objective (by
calculation)
| Identifer | oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/19216 |
| Date | January 2020 |
| Creators | Algamudi, Abdulrazag A.M. |
| Contributors | Not named |
| Publisher | University of Bradford, School of Electrical Engineering and computer Science. Faculty of Engineering and Informatics |
| Source Sets | Bradford Scholars |
| Language | English |
| Detected Language | English |
| Type | Thesis, doctoral, MPhil |
| Rights | <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/"><img alt="Creative Commons License" style="border-width:0" src="http://i.creativecommons.org/l/by-nc-nd/3.0/88x31.png" /></a><br />The University of Bradford theses are licenced under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/">Creative Commons Licence</a>. |
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