Fast Algorithm for Despeckling Sentinel-1 SAR Data
Konferenz: EUSAR 2018 - 12th European Conference on Synthetic Aperture Radar
04.06.2018 - 07.06.2018 in Aachen, Germany
Tagungsband: EUSAR 2018
Seiten: 5Sprache: EnglischTyp: PDFPersönliche VDE-Mitglieder erhalten auf diesen Artikel 10% Rabatt
Kanoun, Bilel; Pascazio, Vito; Schirinzi, Gilda (Dipartimento di Ingegneria, University of Naples Parthenope, Napoli, Italy)
Ferraioli, Giampaolo (Dipartimento di Scienze e Tecnologie, University of Naples Parthenope, Napoli, Italy)
Speckle noise is an inherent dilemma that alters image processing field particularly synthetic aperture radar images. In order to mitigate its adverse effects, different approaches have been proposed in literature in the last twenty years. However, all approaches suffer from some limits. In particular it is very difficult to find an approach able, at the same time, to preserve image details and provide the solution without requiring high computational complexity and time. This paper aims to test a new despeckling algorithm that is able to jointly guarantee the two previous requirements. The algorithm, based on an evolution of Wiener Filter, modified using Markov Random Fields, is tested and compared on a real Sentinel-1 data. The results are interesting and promising: the proposed algorithm turns to be a useful instrument in case large images or stack of images need to be filtered within a limited time, ensuring good detail preservation.