一种空间三维图像的细化算法

摘要

This paper researched three - dimensional image clarity problem. The traditional stereo vision technology was created by three - dimensional model with few data points, which resulted in low three - dimensional model resolution. This paper presented a three-dimensional model of Gaussian wavelet function thinning algorithm based on the existing three-dimensional image point of a small amount of data triangulation, then calculated more three -dimensional data points to increase the composition of three-dimensional data model. The number of points increases the clarity of three-dimensional image model. Experimental results show that the method is fast and efficient, and able to significantly increase the clarity of three-dimensional image model and achieves satisfactory results.%研究三维图像清晰度优化问题,针对传统的通过立体视觉技术创建的三维模型由于组成的数据点过少,造成三维模型清晰度不高.为了提高图像清晰度,提出一种基于高斯小波函数的三维模型细化算法,算法根据已有的少量的三维图像点数据,通过三角剖分,仿真得到更多的三维数据点,增加组成三维模型中数据点的数目,可增加了三维图像模型的清晰度.实验结果表明,方法快速高效,能够大幅增加三维图像模型的清晰度,取得了令人满意的效果.