Strathprints logo
Strathprints Home | Open Access | Browse | Search | User area | Copyright | Help | Library Home | SUPrimo

Optimal Filtering of Solar Images using Soft Morphological Processing Techniques

Marshall, S. and Fletcher, L. and Hough, K. (2006) Optimal Filtering of Solar Images using Soft Morphological Processing Techniques. Astronomy and Astrophysics, 457 (2). pp. 729-736. ISSN 0004-6361

Full text not available in this repository. (Request a copy from the Strathclyde author)

Abstract

CCD images obtained by space-based astronomy and solar physics are frequently spoiled by galactic and solar cosmic rays, and particles in the Earth's radiation belt, which produces an overlaid, often saturated, speckle. We describe the development and application of a new image-processing technique for the removal of this noise source, and apply it to SOHO/LASCO coronagraph images. We employ soft morphological filters, a branch of non-linear image processing originating from the field of mathematical morphology, which are particularly effective for noise removal. The soft morphological filters result in a significant improvement in image quality, and perform significantly better than other currently existing methods based on frame comparison, thresholding, or simple morphologies. This is a promising and adaptable technique that should be extendable to other space-based solar and astronomy datasets.

Item type: Article
ID code: 11604
Keywords: data analysis , image processing , corona , sun, coronal mass ejections, CMEs, Electrical engineering. Electronics Nuclear engineering, Astronomy and Astrophysics, Space and Planetary Science
Subjects: Technology > Electrical engineering. Electronics Nuclear engineering
Department: Faculty of Engineering > Electronic and Electrical Engineering
Unknown Department
Related URLs:
    Depositing user: Strathprints Administrator
    Date Deposited: 07 Nov 2011 12:42
    Last modified: 04 Sep 2014 20:10
    URI: http://strathprints.strath.ac.uk/id/eprint/11604

    Actions (login required)

    View Item