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SAR 图像的统计建模：综述。

Statistical modeling of SAR images: a survey.

机构信息

National University of Defence Technology, Changsha 410073, China.

出版信息

Sensors (Basel). 2010;10(1):775-95. doi: 10.3390/s100100775. Epub 2010 Jan 21.

DOI:10.3390/s100100775
PMID:22315568
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3270869/
Abstract

Statistical modeling is essential to SAR (Synthetic Aperture Radar) image interpretation. It aims to describe SAR images through statistical methods and reveal the characteristics of these images. Moreover, statistical modeling can provide a technical support for a comprehensive understanding of terrain scattering mechanism, which helps to develop algorithms for effective image interpretation and creditable image simulation. Numerous statistical models have been developed to describe SAR image data, and the purpose of this paper is to categorize and evaluate these models. We first summarize the development history and the current researching state of statistical modeling, then different SAR image models developed from the product model are mainly discussed in detail. Relevant issues are also discussed. Several promising directions for future research are concluded at last.

摘要

统计建模对于 SAR（合成孔径雷达）图像解译至关重要。它旨在通过统计方法来描述 SAR 图像，并揭示这些图像的特征。此外，统计建模可以为全面了解地形散射机制提供技术支持，从而有助于开发有效的图像解译和可信的图像模拟算法。已经开发了许多统计模型来描述 SAR 图像数据，本文旨在对这些模型进行分类和评估。我们首先总结了统计建模的发展历史和当前研究状况，然后主要详细讨论了从乘积模型发展而来的不同 SAR 图像模型。还讨论了相关问题。最后得出了几个有前途的未来研究方向。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3bc/3270869/80d8f39b5a03/sensors-10-00775f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3bc/3270869/8bcbf137eea3/sensors-10-00775f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3bc/3270869/db8ffc7de6d2/sensors-10-00775f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3bc/3270869/2c6b28dcbe28/sensors-10-00775f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3bc/3270869/35d35f57b5f4/sensors-10-00775f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3bc/3270869/678216044069/sensors-10-00775f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3bc/3270869/6e9d04e123a8/sensors-10-00775f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3bc/3270869/80d8f39b5a03/sensors-10-00775f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3bc/3270869/8bcbf137eea3/sensors-10-00775f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3bc/3270869/db8ffc7de6d2/sensors-10-00775f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3bc/3270869/2c6b28dcbe28/sensors-10-00775f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3bc/3270869/35d35f57b5f4/sensors-10-00775f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3bc/3270869/678216044069/sensors-10-00775f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3bc/3270869/6e9d04e123a8/sensors-10-00775f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3bc/3270869/80d8f39b5a03/sensors-10-00775f7.jpg

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