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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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Journal ArticleDOI

A change detection measure based on a likelihood ratio and statistical properties of SAR intensity images

TL;DR: The histogram of this change detection measure deduced from the likelihood ratio has a single and steep peak that can be used to reliably and easily determine the change detection threshold.
Book ChapterDOI

Change Detection Techniques: A Review

TL;DR: In this article, a review of change detection techniques using multitemporal remotely sensed images is presented, which includes data preprocessing, change image generation and change detection algorithms such as unsupervised and supervised change detection as well as pixel-based and object-based change detection.
Journal ArticleDOI

Blind Speckle Decorrelation for SAR Image Despeckling

TL;DR: The experimental results show that the despeckling filters achieve better performance when they are preceded by the proposed whitening method; furthermore, the radiometric characteristics of the image are preserved.
Journal ArticleDOI

Effect of the Vegetation Fire on Backscattering: An Investigation Based on Sentinel-1 Observations

TL;DR: The results reveal a significant decrease of the VH response over the fire-disturbed forests, thus, highlighting the effectiveness of such cross-polarized observations in detecting fire scars in vegetated areas at regional scale.
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