Jan 3, 2022 · This article proposes a nonlocal low-rank point cloud denoising framework (NL-PCD) to handle 3-D measurement surfaces with different-scale and -type noise.
This article proposes a nonlocal low-rank point cloud denoising framework (NL-PCD) to handle 3-D measurement surfaces with different-scale and -type noise. We ...
This paper proposes a non-local low-rank point cloud denoising framework (NL-PCD) to handle 3D measurement surfaces with different-scale and -type noise. We ...
This article proposes a nonlocal low-rank point cloud denoising framework (NL-PCD) to handle 3-D measurement surfaces with different-scale and -type noise. We ...
Dive into the research topics of 'Nonlocal Low-Rank Point Cloud Denoising for 3-D Measurement Surfaces'. Together they form a unique fingerprint.
In this paper, we propose a novel point cloud denoising algorithm based on the characteristics of non-local self-similarity.
ABSTRACT: This article addresses the problem of denoising 3D data from LIDAR. It is a step often required to allow a good reconstruction of surfaces represented ...
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Non-Local Denoising. LR. Low Rank. B. Graph Laplacian Regularizer. Graph signal refers to data that resides on the nodes of a graph, such as functionality of ...
This paper attempts to model similar local patterns in a single 3D point cloud and aggregate them to generate feature-preserving point set surfaces.
Dec 1, 2021 · In this paper, we propose a novel point cloud denoising algorithm based on the characteristics of non-local self-similarity. First, we present ...