Non-local collaborative denoising via weighted nuclear norm minimization for point cloud

Xinyu Chen; Guanghao Du; Zhipeng Shi; Yiping Zhao

doi:10.1117/12.3029701

21 June 2024 Non-local collaborative denoising via weighted nuclear norm minimization for point cloud

Xinyu Chen, Guanghao Du, Zhipeng Shi, Yiping Zhao

Proceedings Volume 13167, International Conference on Remote Sensing, Mapping, and Image Processing (RSMIP 2024); 1316710 (2024) https://doi.org/10.1117/12.3029701
Event: International Conference on Remote Sensing, Mapping and Image Processing (RSMIP 2024), 2024, Xiamen, China

Abstract

In order to suppress noise in 3D point clouds while preserving geometric features, a non-local collaborative denoising method based on weighted nuclear norm minimization is proposed. Firstly, an iterative weighted PCA algorithm is used for preliminary normal estimation, followed by bilateral filtering and normal-based PCA for refinement. The eigenvectors of the covariance matrix constructed from the neighboring points can form the local coordinate system. Then the local point cloud is projected and transformed into a height-map patch. Subsequently, to reduce the difficulty of constructing similar structures, similar height maps are searched in the global point clouds, and assembled to form the low-rank height map patch group matrix, which is considered as a descriptor of non-local similar structures. Subsequently, the weighted nuclear norm minimization is applied for low-rank matrix recovery, thereby reducing the noise of local point clouds. Finally, the denoised local point clouds are combined to form the global point cloud, realizing non-local collaborative denoising. Based on updated positions, a projection optimization algorithm is used to recover sharp features. Experiment results indicate that the proposed method effectively reduces noise while preserving the original features of the point cloud.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xinyu Chen, Guanghao Du, Zhipeng Shi, and Yiping Zhao "Non-local collaborative denoising via weighted nuclear norm minimization for point cloud", Proc. SPIE 13167, International Conference on Remote Sensing, Mapping, and Image Processing (RSMIP 2024), 1316710 (21 June 2024); https://doi.org/10.1117/12.3029701

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KEYWORDS

Point clouds

Matrices

Denoising

Principal component analysis

Tunable filters

Reconstruction algorithms

Eigenvectors

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