A discernible criterion for 3D point cloud based on multifractal spectrum

Kun Yu, Jie Ma, Bin Fang, Bingli Wu
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Abstract

The traditional discernible criteria for a 2D target are mostly based on Johnson criterion, to overcome the limitations of the Johnson criterion and fill the gap in a 3D point cloud, a novel discernible criterion has been proposed for the 3D point cloud. Based on the multifractal spectrum, the spatial distribution of the 3D point cloud is described. By analyzing the multifractal spectra at different resolutions, feature trend and the final discernible resolution are concluded. The experimental results show that the limiting resolution of T90, F15C is 585mm, the limiting resolution of T90 and Rexton is 517mm, and the limiting resolution of F15C and Rexton is 541mm. The proposed discernible criteria can provide theoretical support for limit identification resolution of 3D point cloud target.
基于多重分形谱的三维点云识别准则
传统的二维目标识别准则多基于Johnson准则,为了克服Johnson准则的局限性,填补三维点云的空白,提出了一种新的三维点云识别准则。基于多重分形谱,描述了三维点云的空间分布。通过对不同分辨率多重分形光谱的分析,得出了特征趋势和最终的可分辨分辨率。实验结果表明,T90、F15C的极限分辨率为585mm, T90和Rexton的极限分辨率为517mm, F15C和Rexton的极限分辨率为541mm。所提出的识别准则可为三维点云目标的极限识别分辨率提供理论支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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