基于多通道分类合成的SAR图像分类研究

Research on SAR Image Classification Based on Composing Multi-channel Data

SAR具有全天时、全天候工作能力,且能够提供高分辨率图像数据。SAR图像分类是SAR图像处理的关键步骤。目前,SAR图像分类多是基于单通道图像数据。多通道SAR数据极大地丰富了地物目标信息量,利用多通道数据进行分类,是SAR图像分类的重要发展方向。本文提出基于多通道分类合成的SAR图像分类算法。该算法首先利用SVM对不同通道的数据分别进行分类,然后利用粒度合成理论对不同的分类结果进行合并,最后实现多通道SAR数据图像分类。本文重点论述了利用该方法进行SAR图像分类的基本流程和步骤。最后,结合实验结果,证明了该算法的可行性和有效性。

SAR has the ability to work all weather, and can provide high resolution remote sensing images, so it is an important direction to study. The SAR image classification is a key step for SAR processing. At present, the study on SAR image classification is mostly based on single-channel data, multi-channel data tins greatly enriched the information amount of ground target features, taking use of muhi-channel data to carry out SAR image classification is an important development direction. In the paper, the classification method of composing muhi-channel data classification results is proposed. Firstly, the method is to use different channel data to classify separately by SVM, then composes different classification results based on granularity composition theory. The paper mainly focuses on the basic flow and steps of this method. In the end, an experiment of using single-channel data to classify and merging muhi-channel data features to classify is done, the result proves the method of this paper is viable.