Very-high-resolution and interferometric SAR: Markovian and patch-based non-local mathematical models

Charles Alban Deledalle, Loïc Denis, Giampaolo Ferraioli, Vito Pascazio, Gilda Schirinzi, Florence Tupin

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

This chapter is dedicated to very-high-resolution (VHR) SAR imagery, including interferometric applications. First, the principles of SAR data acquisition are presented as well as the different types of configurations. The widely adopted Gaussian complex model of fully developed speckle is described as well as more advanced statistical models for VHR SAR data that account for textures. The following two parts are devoted to SAR image estimation and to image denoising within two different frameworks. First, Markovian modeling is introduced and the associated optimization approaches are presented, including graph-cut-based optimization. The second framework is the patch-based non-local modeling of SAR complex data. Both frameworks are adapted to SAR images through the use of statistical models specific to SAR imagery. Their applications to amplitude data, interferometry, and fusion with optical data are illustrated. A special focus is given to phase unwrapping applied to single- and multi-channel interferometry, showing the usefulness of local and global contextual models.

Original languageEnglish
Title of host publicationSignals and Communication Technology
PublisherSpringer Science and Business Media Deutschland GmbH
Pages137-189
Number of pages53
DOIs
Publication statusPublished - 1 Jan 2018
Externally publishedYes

Publication series

NameSignals and Communication Technology
ISSN (Print)1860-4862
ISSN (Electronic)1860-4870

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