基于多光谱融合的三维视觉重建系统

3D Visual Reconstruction System Based on Multispectral Fusion

为了解决目标三维重建时杂散点干扰、数据空洞等问题,提高三维视觉重建效果,提出了基于偏振多光谱融合的三维视觉重建算法。搭建了双目激光扫描与偏振多光谱成像系统,利用本融合算法将多光谱映射的特征区域作为目标三维点云在该截面的二维边界,完成了点云滤波。测试了高斯采样与极值采样方式的解算精度,映射位置与实际位置的偏差均值分别为0.59 mm与0.93 mm。采用4种偏振片的叠加降噪处理后,背景区域噪声强度均值由49.5降低为13.4。对包含两个局部曲率不同的目标特征进行测试发现,优化后,超过80%的测试点的误差优于3.05μm,平均偏差为1.49μm,目标三维视觉重建效果得到了改善。

To solve the problems of scattered point interference and data holes in 3D target reconstruction,and to improve the 3D visual reconstruction effect,a 3D visual reconstruction algorithm based on polarization multispectral fusion was proposed.A binocular laser scanning and polarization multispectral imaging system was built,and a fusion algorithm was used to filter the point cloud by considering the characteristic region of multispectral mapping as the two-dimensional boundary of the target 3D point cloud.The precision of Gaussian and extremum sampling was tested experimentally.The mean deviation between the mapping position and the actual position was 0.59 mm and 0.93 mm,respectively.The average noise intensity in the background area was reduced from 49.5 to 13.4 after the superposition of four polarizers for noise reduction.Testing the target features with two different local curvatures determined that after optimization,over 80%of the test points had an error better than 3.05μm,with an average deviation of 1.49μm.Moreover,the 3D visual reconstruction effect of the target was improved.