计算机应用与软件2016，Vol.33Issue(12)：169-172,206,5.DOI:10.3969/j.issn.1000-386x.2016.12.041
基于频率直方图的K邻域稀疏离群点移除算法
K-NEAREST NEIGHBORS SPARSE OUTLIER REMOVAL ALGORITHM BASED ON FREQUENCY HISTOGRAM
摘要
Abstract
At the point cloud preprocessing stage,there are still some deficiencies existing in the traditional sparse outlier removal algo-rithm based on k-nearest neighbors.In the point cloud processing,there is no proper selection scheme about the size of the k-nearest neighbors and the noise threshold of the sparse outliers which will be eliminated.According to the analysis and research of the traditional k-nearest neighbors sparse outlier removal algorithm of scattered point cloud,an analysis method of statistical histogram based on the k-nearest neighbors average distance is proposed,improving the distribution of the traditional sparse outlier removal based on k-nearest neighbors.This method is able to select the reasonable k value and the noise threshold effectively.This method generates the frequency statistical histogram of k-nearest neighbor’s average distance and analyzes the statistical histogram so as to determine the appropriate value of k-nearest neighbors by setting the k values of the scattered point cloud in successive increase.According to the proper k value,it selects the reasonable noise threshold and car-ries out de-noising.Through this method,it provides the theoretical basis for the selection of k value and noise threshold in the sparse outlier removal algorithm,and improves the efficiency of point cloud search and prevents the excessive deletion of outliers at the same time.关键词
散乱点云/稀疏离群点/k 近邻/直方图/密度特征Key words
Scattered point cloud/Sparse outliers k-nearests neighbor/Frequency histogram/Density character分类
信息技术与安全科学引用本文复制引用
郭子选,谢晓尧,刘嵩..基于频率直方图的K邻域稀疏离群点移除算法[J].计算机应用与软件,2016,33(12):169-172,206,5.基金项目
贵州省科技厅工业攻关项目（黔科合GZ字［2012］3017）；贵州省科学技术基金项目（黔科合 J 字 LKS［2011］9号）；贵州省经济和信息化委员会项目（1158）。 （）
