基于反射光强度和深度二维变量的含加性权值B样条曲面误差拟合被用于校正由目标场景的低反射率或长距离引起的弱光强度相关深度误差。与传统的B样条曲面误差拟合相比,改进的模型使用权值参数优化每个曲面片的部分控制点,获得了更精确的误差拟合曲面片,使得平均校正误差小于2 mm,精度提高了近2倍。此外,为克服乘性权值矩阵无法通过最小二乘法获取的难题,对每个控制点添加加性权值参数,实现相机参数校准过程中一次性求得控制点参数矩阵和加性权值参数矩阵。同时,考虑到谐波相关误差也与深度相关,将谐波相关误差的校正统一到校正方法中。

This study uses a B-spline surface error fitting function based on reflected light intensity and depth two-dimensional variable with additive weights to correct the weak light intensity-related depth error that occurs because of the low reflectivity or long distance of the target scene. In contrast to the traditional B-spline surface error fitting, the improved model uses weight parameters to optimize partial control points of each surface to obtain a more accurate error-fitting surface. It allows average correction errors to be less than 2 mm, which is nearly three times the accuracy of the traditional model. Furthermore, the additive weight parameter is added to each control point, which ensures that the parameter matrices of control points and additive weight can be obtained in a single step during the camera parameter calibration process,overcoming the issue that the multiplicative weight matrix cannot be obtained by the least squares method. Moreover, considering that the harmonic-related error is also connected to depth, the correction of the harmonic-related error is unified into the proposed correction method.