Abstract
The increasing availability of synthetic aperture radar (SAR) time series creates many opportunities for remote sensing applications, but it can be challenging in terms of amount of data to process. This letter discusses the interest of the geometric mean to average SAR time series. First, the properties of the geometric mean and the arithmetic mean are compared. Then, a speckle-reduction method specifically designed to improve images obtained with the geometric mean is presented. This method is based on an adaptation of the MuLoG framework to take into account the specific distribution of the geometric mean. Finally, applications of this denoised geometric-mean image are presented.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
