常州大学学报（自然科学版）2012，Vol.24Issue(1)：69-72,4.
一种快速散乱点自适应滤波方法
Fast Self-Adaptive Method for Scatter Point Cloud Denoising
摘要
Abstract
Denoising is an essential step in creating perfect point - sampled models. Liang Xinhe extends image mean-shift filtering to 3D surface smoothing by taking the vertex normal and curvature as range component and the vertex position as the spatial component, which is not efficient. For this reason, this paper proposes to use quasi - Cauchy kernel to replace the Gauss kernel used in the Guofei. Hu' algorithm. Experiments show that our method can smooth the noise efficiently and preserve the sharp features of the surface effectively.关键词
点模型/自适应/高斯核函数/柯西核函数/降噪Key words
point-sampled model/ self-adaptive/ gauss kernel/ cauchy kernel/ denosing分类
信息技术与安全科学引用本文复制引用
顾晓清,马正华,侯振杰,倪彤光..一种快速散乱点自适应滤波方法[J].常州大学学报（自然科学版）,2012,24(1):69-72,4.基金项目
国家自然科学基金项目(61063021) （61063021）
