Independent component analysis for sea ice SAR image classification

IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217) Pub Date : 2001-07-09 DOI:10.1109/IGARSS.2001.976810

J. Karvonen, M. Simila

引用次数: 15

Abstract

Independent component analysis (ICA) is used to compute sets of basis vectors for image data, i.e. for small randomly selected image windows. From these basis vectors a smaller set is selected to be used in classifying sea ice SAR images. A SAR image window is classified based on its projection to the selected basis vectors.

查看原文本刊更多论文

海冰SAR图像分类的独立分量分析

独立分量分析(ICA)用于计算图像数据的基向量集，即随机选择的小图像窗口。从这些基向量中选择一个较小的基向量集用于海冰SAR图像的分类。SAR图像窗口的分类是基于其在选定基向量上的投影。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217)

自引率

0.00%

发文量