Empirical Radiometric Normalization of Road Points from Terrestrial Mobile Lidar System

Remote Sensing

Tee-Ann Teo¹  Hui-Lin Yu²  Juha Hyyppä² 

[1] Department of Civil Engineering, National Chiao Tung University, Hsinchu 30010, Taiwan; E-Mail

关键词: MLS;    radiometric normalization;    data driven;    amplitude;    road surface classification;   

DOI  :  10.3390/rs70506336

来源: mdpi

【 摘 要 】

Lidar data provide both geometric and radiometric information. Radiometric information is influenced by sensor and target factors and should be calibrated to obtain consistent energy responses. The radiometric correction of airborne lidar system (ALS) converts the amplitude into a backscatter cross-section with physical meaning value by applying a model-driven approach. The radiometric correction of terrestrial mobile lidar system (MLS) is a challenging task because it does not completely follow the inverse square range function at near-range. This study proposed a radiometric normalization workflow for MLS using a data-driven approach. The scope of this study is to normalize amplitude of road points for road surface classification, assuming that road points from different scanners or strips should have similar responses in overlapped areas. The normalization parameters for range effect were obtained from crossroads. The experiment showed that the amplitude difference between scanners and strips decreased after radiometric normalization and improved the accuracy of road surface classification.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.