CUDA based Point Cloud Denoising Algorithm

This paper proposes a Compute Unified Device Architecture(CUDA)-based improved bilateral filtering point cloud denoising algorithm.The point cloud denoising algorithm is divided into several steps in a very high degree of parallelism.It separately designs CUDA kernel functions for each step,effectively emploies the GPU's parallel computing power.It uses Gaussian-weighted method of calculating normal vector and effectively improves the accuracy of normal vector calculation.The bilateral denoising algorithm adds the weight of the area to alleviate the excessive smoothing.Experimental results show that the algorithm is stable and efficient,faster than the CPU calculation of multiple orders of magnitude.