多核学习在遥感图像分类中的比较研究

2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) Pub Date : 2016-07-10 DOI:10.1109/IGARSS.2016.7729386

S. Niazmardi, B. Demir, L. Bruzzone, A. Safari, Saeid Homayouni

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引用次数: 8

摘要

本文对不同的多核学习(Multiple Kernel Learning, MKL)遥感图像分类算法进行了分析比较。比较的主要目的是找出不同的MKL算法在计算时间和分类精度方面的优缺点。在此基础上，针对不同的遥感图像分类问题，给出了适当选择MKL算法的指导原则。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A comparative study on Multiple Kernel Learning for remote sensing image classification

This paper analyzes and compares different Multiple Kernel Learning (MKL) algorithms for the classification of remote sensing (RS) images. The main purpose of the comparison is to identify advantages and disadvantages of different MKL algorithms in terms of their computational time and classification accuracy. Furthermore, some guidelines on the proper selection of the MKL algorithms associated with different RS image classification problems are derived.

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2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

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