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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.read more
Citations
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Journal ArticleDOI
Synthetic aperture fourier holographic optical microscopy.
TL;DR: Synthetic microscopic imaging is demonstrated in which spatial frequencies that are well outside the modulation transfer function of the collection optical system are recorded while maintaining the long working distance and wide field of view.
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A review of polarimetry in the context of synthetic aperture radar: concepts and information extraction
TL;DR: In this article, the authors provide an update of the polarimetric tools currently being used for optimum information extraction from polarIMetric synthetic aperture radar (SAR) images, including the use of coherent versus incoherent target decomposition and the practical limitations of these target decompositions.
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Semi-empirical model of the ensemble-averaged differential Mueller matrix for microwave backscattering from bare soil surfaces
TL;DR: A semi-empirical model of the ensemble-averaged differential Mueller matrix for microwave backscattering from bare soil surfaces is presented, specifying completely the degree of correlation and the co-polarized phase-difference probability density function.
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A SAR Dataset of Ship Detection for Deep Learning under Complex Backgrounds
TL;DR: Experimental results reveal that object detectors achieve higher mean average precision (mAP) on the test dataset and have high generalization performance on new SAR imagery without land-ocean segmentation, demonstrating the benefits of the dataset the authors constructed.
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Automatic Target Recognition in Synthetic Aperture Radar Imagery: A State-of-the-Art Review
TL;DR: A two-fold benchmarking scheme for evaluating existing SAR-ATR systems and motivating new system designs is proposed, and a taxonomization methodology for surveying the numerous methods published in the open literature is proposed.