离散点云数据的小波变换处理算法

Method of Data Processing for Discrete Cloud Based on Wavelet Transform

将离散点云数据表示成适合用作小波变换的形式,提出了一种基于尺度的离散点云数据的特征识别算法,在此基础上给出了具体的基于尺度的二维和三维离散点云的小波分解算法,最后引入实例对二维离散点云的小波分解算法进行分析,实验结果表明算法达到了对点云数据的按尺度特征分解的目的.通过提出的算法,将离散点云数据按照尺度进行分解并提取出不同的特征成分,这样可以根据后期可视化显示的不同要求,将小波变换分解后的数据进行进一步的处理.

This paper presents a feature recognition algorithm for discrete cloud points based on dimension information and a detailed wavelet decomposition method for 2D and 3D discrete cloud points. 128 discrete points are adopted to analyze the algorithm,and it is found the result of this example meet the requirement for discrete cloud wavelet decomposition. The discrete cloud points are decomposed and different features are extracted according to its dimension information, and these decomposed data can be further processed to meet different visualization display requirement.