RT Journal Article
T1 Realistic correction of sky-coloured points in Mobile Laser Scanning point clouds
A1 Gonzalez Rodriguez, Maria Elena
A1 Balado Frías, Jesús
A1 Arias Sánchez, Pedro
A1 Lorenzo Cimadevila, Henrique Remixio
K1 331102 Ingeniería de control
AB The enrichment of the point clouds with colour images improves the visualisation of the data as well as the segmentation and recognition processes. Coloured point clouds are becoming increasingly common, however, the colour they display is not always as expected. Errors in the colouring of point clouds acquired with Mobile Laser Scanning are due to perspective in the camera image, different resolution or poor calibration between the LiDAR sensor and the image sensor. The consequences of these errors are noticeable in elements captured in images, but not in point clouds, such as the sky. This paper focuses on the correction of the sky-coloured points, without resorting to the images that were initially used to colour the whole point cloud. The proposed method consists of three stages. First the region of interest where the erroneously coloured points are accumulated, is selected. Second, the sky-coloured points are detected by calculating the colour distance in the Lab colour space to a sample of the sky-colour. And third, the colour of the sky-coloured detected points is restored from the colour of the nearby points. The method is tested in ten real case studies with their corresponding point clouds from urban and rural areas. In two case studies, sky-coloured points were assigned manually and the remaining eight case studies, the sky-coloured points are derived from the acquisition errors. The algorithm for sky-coloured points detection obtained an average F1-score of 94.7%. The results show a correct reassignment of colour, texture, and patterns, while improving the point cloud visualisation.
PB Optics & Laser Technology
SN 00303992
YR 2022
FD 2022-05
LK http://hdl.handle.net/11093/2920
UL http://hdl.handle.net/11093/2920
LA eng
NO Optics & Laser Technology, 149, 107807 (2022)
NO Financiado para publicación en acceso aberto: Universidade de Vigo/CISUG
NO Xunta de Galicia | Ref. ED481B-2019-061
DS Investigo
RD 17-sep-2024