An end-user-oriented framework for the classification of multitemporal SAR images

被引：13

作者：

Amitrano D. ^{[1
]}

Di Martino G. ^{[1
]}

Iodice A. ^{[1
]}

Riccio D. ^{[1
]}

Ruello G. ^{[1
]}

机构：

[1] Department of Electrical Engineering and Information Technology, University of Napoli Federico II, Naples

来源：

International Journal of Remote Sensing | 2016年 / 37卷 / 01期

关键词：

Radar imaging - Image classification;

D O I：

10.1080/01431161.2015.1125550

中图分类号：

学科分类号：

摘要：

In this article, we present an end-user-oriented framework for multitemporal synthetic aperture radar (SAR) data classification. It accepts as input the recently introduced Level-1α products, whose peculiarities are a high degree of interpretability and increased class separability with respect to single greyscale images. These properties make the Level-1α products very attractive in the application of simple supervised classification algorithms. Specifically, (1) the high degree of interpretability of the maps makes the training phase extremely simple; and (2) the good separation between classes gives excellent results using simple discrimination rules. The end product is a simple, fast, accurate, and repeatable framework. © 2015 Taylor & Francis.

引用

页码：248 / 261

页数：13

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