Autonomous Building Detection Using Region Properties and PCA

N. Aburaed, A. Panthakkan, Husameldin Mukhtar, W. Mansoor, S. Almansoori, Hussain Al-Ahmad
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引用次数: 2

Abstract

This paper proposes an algorithm for autonomous building detection in remote sensing images. The basis of the algorithm relies on the fact that each channel in RGB color space conveys different information. Furthermore, region properties and Principal Component Analysis (PCA) are used to distinguish between buildings and other regions in order to reduce false positive cases. The images used to test the proposed algorithm were obtained from DubaiSat-2, which offers multispectral images with 1-m accuracy.
基于区域属性和PCA的自主建筑检测
提出了一种基于遥感图像的建筑物自主检测算法。该算法的基础依赖于RGB色彩空间中每个通道传递不同信息的事实。此外,利用区域属性和主成分分析(PCA)来区分建筑物和其他区域,以减少误报情况。用于测试该算法的图像来自DubaiSat-2,该卫星提供精度为1米的多光谱图像。
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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