基于分形描述的SAR图像特征提取与分类

6th International Conference on Signal Processing, 2002. Pub Date : 2002-08-26 DOI:10.1109/ICOSP.2002.1180052

Jia Xu, Ling Lu, Zhenming Feng, Yingning Peng

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引用次数: 3

摘要

在合成孔径雷达(SAR)图像分析领域，提出了一种基于分形布朗增量随机场(FBRIR)的有效特征提取方法，并据此设计了一种基于自适应共振理论(ART)的神经元网络分类方法。最后，利用Ku波段SAR图像的实际数据对该方法的有效性进行了验证和比较。

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SAR image feature extraction and classification with fractal-based description

In the field of synthetic aperture radar (SAR) image analysis, an effective feature extraction method based on a fractal Brownian increment random field (FBRIR) is introduced, and an effective classification method with a neuron network based on adaptive resonance theory (ART) is designed accordingly. At last the validity of this systematic approach is tested and compared using real data of Ku band SAR images.

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6th International Conference on Signal Processing, 2002.

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