光学学报, 2009, 29 (3): 733, 网络出版: 2009-03-17
基于统计逼近的Stoilov改进算法
An Improved Stoilov Algorithm Based on Statistical Approach
信息光学 三维测量 Stoilov算法 统计逼近 相位误差 算法改进 information optics three-dimensional measurement Stoilov algorithm statistical approach phase error algorithm improvement
摘要
Stoilov算法是近几年提出的一种相移量任意的等步长相移算法,它无须知道相移量的大小,只要保证相移步长相等,就可以解算出物体表面的截断相位,因而在三维测量领域中倍受人们关注。但Stoilov算法的表达式过分依赖采集的变形条纹图像的光强,存在对光强的减法、除法和开方等运算,使相位计算时在某些位置会出现分子分母为零,开方出现复数等奇异现象,会导致算法算错或者相位展开出错,致使三维重构表面会出现畸变、失真,甚至无法进行三维重构。因此提出了一种基于统计逼近的方法对Stoilov算法进行修正,有效抑制了奇异现象引入的相位误差,提高了三维测量精度。实验验证了其算法的有效性和适用性。
Abstract
Stoilov algorithm is a recently developed equivalent step algorithm whose phase step is arbitrary. The value of the phase shifting needn’t be known but phase step must remain invariable. The wrap phase caused by measured object can be derived correctly. So it is paid wide attention in three-dimensional measurement field. However, Stoilov algorithm excessively depends on the intensity of the image, and subtraction, division and extraction must be operated in its mathematical model. Imaging process will cause some abnormal phenomena somewhere such as the zeroth denominator and complex phase, which lead to the incorrect phase calculation or incorrect phase unwrapping. The reconstructed object will be misshapen or anamorphic, or even the measured object can’t be reconstructed. So a new method based on the statistical approach to improve Stoilov algorithm has been proposed. By this method the phase error brought by the abnormal phenomena is restrained and the precision of three-dimensional measurement is improved. Experiments show its feasibility and validity.
许幸芬, 曹益平. 基于统计逼近的Stoilov改进算法[J]. 光学学报, 2009, 29(3): 733. Xu Xingfen, Cao Yiping. An Improved Stoilov Algorithm Based on Statistical Approach[J]. Acta Optica Sinica, 2009, 29(3): 733.