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Understanding Synthetic Aperture Radar Images

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TLDR
In this paper, the principles of SAR image image formation are discussed and an analysis technique for multi-dimensional image analysis is presented based on RCS Reconstruction Filters and Texture Exploitation.
Abstract
Introduction. Principles of SAR Image Formation. Image Defects and their Correction. Fundamental Properties of SAR Images. Data Models. RCS Reconstruction Filters. RCS Classification and Segmentation. Texture Exploitation. Correlated Textures. Information in Multi-Channel SAR. Analysis Techniques for Multi-Dimensional Images. Target Information. Image Classification.

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Citations
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A Comparative Study of Sea Clutter Covariance Matrix Estimators

TL;DR: This letter provides a comprehensive study of four covariance matrix estimators: the maximum likelihood estimators under the Gaussian distribution and the K distribution, an approximation of the latter (AK-ML), and a robust M-estimator.
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Polarimetric SAR Speckle Reduction by Hybrid Iterative Filtering

TL;DR: A hybrid iterative filtering scheme is introduced that is initialized by a polarimetric filter ensuring a high speckle reduction level and applied for few iterations to enhance the spatial details of PolSAR filters.
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Polarimetric Calibration of Circularly Polarized Synthetic Aperture Radar Data

TL;DR: The calibration techniques are applied to fully polarimetric data acquired by the Ingara L-band radar using left- and right-polarized helical antennas, and it is shown that the distortion caused, to first-order, by circular-basis cross-talk does not permit the individual cross- talk parameters to be identified.
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Exploring event landslide mapping using Sentinel-1 SAR backscatter products

TL;DR: In this paper, a team of experts defined interpretation criteria of SAR amplitude post-event images of the backscatter coefficient (β₀) and of the derived images of change.
Proceedings ArticleDOI

Segment-based urban block outlining in high-resolution SAR images

TL;DR: This paper presents a preliminary work on the use of a linear feature extractor, originally developed for road network extraction, as a tool to partition a very high resolution SAR scene acquired over an urban area.
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