Neural Network and Local Laplace Filter Methods Applied to Very High Resolution Remote Sensing Imagery in Urban Damage Detection

被引：0

作者：

Hordiiuk, D. M. ^{[1
]}

Hnatushenko, V. V. ^{[2
]}

机构：

[1] Natl Met Acad Ukraine, Dept Informat Technol & Syst, Dnipro, Ukraine

[2] Oles Honchar Dnipro Natl Univ, Dept Automated Syst Informat Proc, Dnipro, Ukraine

来源：

2017 IEEE INTERNATIONAL YOUNG SCIENTISTS FORUM ON APPLIED PHYSICS AND ENGINEERING (YSF) | 2017年

关键词：

remote sensing; high spatial resolution; image; neural network; Laplace filter;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

This article is devoted to technology of change detection on satellite imagery. The aim was the development new accurate method to detect ruined buildings after disaster by using satellite images before and after event. The proposed two approaches has been tested on satellite images. Comparison of quantitative indicators (number of right detected houses, number of wrong recognition) as well as the visual results show the advantage of using the proposed technology. The results can be used for further object detection and recognition for change detection of aerospace images.

引用

页码：363 / 366

页数：4

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