On the Use and Denoising of the Temporal Geometric Mean for SAR Time Series

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.

Automated summary

The letter discusses the use of geometric mean in averaging SAR time series, compares its properties with arithmetic mean, and presents a speckle-reduction method specifically designed for improving images obtained with geometric mean.