LASER SCANNER INTENSITY CALIBRATION BASED ON ARTIFICIAL NEURAL NETWORKS

被引：0

作者：

de Figueiredo, Rodrigo M. ^{[1
]}

Veronez, Mauricio R. ^{[1
,2
]}

Tognoli, Francisco M. W. ^{[1
,2
]}

da Silva, Marcio R. ^{[2
]}

Bordin, Fabiane

Gonzaga, Luiz, Jr. ^{[3
]}

Koch, Ismael ^{[2
]}

Marson, Fernando P. ^{[2
]}

Larocca, Ana P. C. ^{[3
]}

机构：

[1] Vale Rio dos Sinos Univ UNISINOS, Grad Program Geol, Sao Leopoldo, Brazil

[2] Univ Vale Rio dos Sinos, VIZLab Adv Visualizat & Geoinformat Lab, Sao Leopoldo, Brazil

[3] Univ Sao Paulo, Sao Carlos Engn Sch, Grad Program Transportat Engn, Sao Carlos, SP, Brazil

来源：

2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2017年

关键词：

LiDAR; Artificial Neural Networks; Laser Intensity; Calibration;

D O I：

暂无

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

In this study, we propose a method to calibrate the laser pulse return intensity of a Terrestrial Laser Scanner (TES) based on Artificial Neural Networks. The laser pulse return intensity has an important rule on rocks types' classification when using Digital Outcrops Models (DOM) and has been the focus of much research by the geological community as it helps the geological interpretation in outcrops. In our experiment, we used a TLS IIris 3D model with a wavelength of 1,535 nn. Our method has shown good efficiency for the calibration of the laser pulse return intensity, demonstrating a strong applicability for classification studies of rock types on Digital Outcrops Models.

引用

页码：1716 / 1719

页数：4

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