A Novel despeckling framework for Ultra-high Resolution SAR Images Based on Complex Generalized Gaussian distribution
Conference: EUSAR 2018 - 12th European Conference on Synthetic Aperture Radar
06/04/2018 - 06/07/2018 at Aachen, Germany
Proceedings: EUSAR 2018
Pages: 6Language: englishTyp: PDFPersonal VDE Members are entitled to a 10% discount on this title
Wu, Wenjin; Li, Xinwu (Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, China)
The complex noise behavior and rich details make it very hard to achieve effective noise reduction and detail preservation at the same time for ultra-high resolution (UHR) SAR images. Therefore, an extendable despeckling framework that employs the complex generalized Gaussian distribution (CGGD) to distinguish structural areas and distributed areas and filters them separately to solve the aforementioned problem is proposed. As an example, a new filter derived from this framework is presented and compared with four state-of-the-art filters. Results demonstrate that the new filter outperforms the other ones and can simultaneously realize excellent structural detail preservation and effective noise reduction.