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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 Multisquint Framework for Change Detection in High-Resolution Multitemporal SAR Images

TL;DR: A three-stage change detector exploiting single-look and multisquint processing mode is proposed to mitigate false alarms caused by image artifacts typically found in high-resolution SAR imagery and urban scenarios.
Journal ArticleDOI

Edge and fine detail preservation in SAR images through speckle reduction with an adaptive mean filter

TL;DR: It is found that the EMDAM filter preserves textures and details while reducing speckle to a desired level and a new testing quantity, the Quality Factor (Q), is introduced.
Journal ArticleDOI

Fast and Adaptive Method for SAR Superresolution Imaging Based on Point Scattering Model and Optimal Basis Selection

TL;DR: A novel fast and adaptive method for synthetic aperture radar (SAR) superresolution imaging that suffers less computation complexity and has better adaptability is developed.
Journal ArticleDOI

Application of Artificial Neural Networks to Ship Detection from X-Band Kompsat-5 Imagery

TL;DR: An efficient method to detect ship targets from X-band Kompsat-5 SAR imagery using the artificial neural network (ANN), and then detects ships from the ship-probability map by using a threshold value is proposed.

A Simple and Extendable Segmentation Method for Multi-Polarisation SAR Images

TL;DR: A simple feature-based multi-channel SAR segmentation method that produces good, smooth, fast and robust results for image segmentation and interpretation and is fast enough for operational use is presented.
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