An approach of point cloud denoising based on improved bilateral filtering

Zeling Zheng; Songmin Jia; Guoliang Zhang; Xiuzhi Li; Xiangyin Zhang

doi:10.1117/12.2303607

10 April 2018 An approach of point cloud denoising based on improved bilateral filtering

Zeling Zheng, Songmin Jia, Guoliang Zhang, Xiuzhi Li, Xiangyin Zhang

Proceedings Volume 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017); 1061557 (2018) https://doi.org/10.1117/12.2303607
Event: Ninth International Conference on Graphic and Image Processing, 2017, Qingdao, China

Abstract

An omnidirectional mobile platform is designed for building point cloud based on an improved filtering algorithm which is employed to handle the depth image. First, the mobile platform can move flexibly and the control interface is convenient to control. Then, because the traditional bilateral filtering algorithm is time-consuming and inefficient, a novel method is proposed which called local bilateral filtering (LBF). LBF is applied to process depth image obtained by the Kinect sensor. The results show that the effect of removing noise is improved comparing with the bilateral filtering. In the condition of off-line, the color images and processed images are used to build point clouds. Finally, experimental results demonstrate that our method improves the speed of processing time of depth image and the effect of point cloud which has been built.

Citation Download Citation

Zeling Zheng, Songmin Jia, Guoliang Zhang, Xiuzhi Li, and Xiangyin Zhang "An approach of point cloud denoising based on improved bilateral filtering", Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 1061557 (10 April 2018); https://doi.org/10.1117/12.2303607

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