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

Nicolas Gasnier; Loic Denis; Florence Tupin

doi:10.1109/LGRS.2021.3051936

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

Nicolas Gasnier
, Loic Denis
, Florence Tupin

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Journal	IEEE Geoscience and Remote Sensing Letters
Volume	19
DOIs	https://doi.org/10.1109/LGRS.2021.3051936
Publication status	Published - 1 Jan 2022

Keywords

Alternating direction method of multiplier (ADMM)
change detection
denoising
geometric mean
multitemporal synthetic aperture radar (SAR) series
speckle reduction
temporal mean
variational methods

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10.1109/LGRS.2021.3051936

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title = "On the Use and Denoising of the Temporal Geometric Mean for SAR Time Series",

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.",

keywords = "Alternating direction method of multiplier (ADMM), change detection, denoising, geometric mean, multitemporal synthetic aperture radar (SAR) series, speckle reduction, temporal mean, variational methods",

author = "Nicolas Gasnier and Loic Denis and Florence Tupin",

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AU - Gasnier, Nicolas

AU - Denis, Loic

AU - Tupin, Florence

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N2 - 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.

AB - 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.

KW - Alternating direction method of multiplier (ADMM)

KW - change detection

KW - denoising

KW - geometric mean

KW - multitemporal synthetic aperture radar (SAR) series

KW - speckle reduction

KW - temporal mean

KW - variational methods

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DO - 10.1109/LGRS.2021.3051936

M3 - Article

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SN - 1545-598X

VL - 19

JO - IEEE Geoscience and Remote Sensing Letters

JF - IEEE Geoscience and Remote Sensing Letters

ER -

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

Abstract

Keywords

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