基本矩阵约束下的摄像机畸变校正及像主点确定  

Camera Distortion Calibration and Principal Point Coordinate Determination Based on Fundamental Matrix

作　　者：程传奇[1] 郝向阳[1] 李建胜[1] 徐海鑫 王安然 CHENG Chuanqi HAO Xiangyang LI Jiansheng XU Haixin WANG Anran(Sehool of Navigation and Aerospaee Engineering, Information Engineering University, Zhengzhou 450001, China Military Representative Offiee of Army Aviation in Harbin, Harbin 150000, China)

机构地区：[1]信息工程大学导航与空天目标工程学院.河南郑州450001 [2]陆航驻哈尔滨地区军代室,黑龙江哈尔滨150000

出　　处：《测绘通报》2017年第9期32-36,45,共6页Bulletin of Surveying and Mapping

基　　金：国家863计划(2015AA7034057A);国家自然科学基金(61173077)

摘　　要：针对视觉测量系统中畸变校正过程烦琐、计算复杂等问题,提出了一种基于基本矩阵约束的镜头畸变自动校正及像主点坐标确定方法。基于对极几何的基本矩阵和一阶径向畸变模型构建了两视图同名点约束方程;为解决待求参数过多导致解不稳定的问题,采用分步求解策略分别求解基本矩阵及畸变参数和主点坐标,用RANSAC稳健估计方法求取基本矩阵,用迭代最小二乘优化求解畸变参数和主点坐标,两步交替进行。提出的算法仅使用两张图像即可获取径向畸变参数及主点坐标,可操作性强,且对噪声具有一定的鲁棒性,适用于自然场景图像的校正。To solve the problem of complicated distortion correction process and complicated calculation in the vision measurement system, method for camera distortion calibration and principal point coordinate determination based on fundamental matrix is proposed. Based on epipolar geometry and single parameter correction model, the equation of correspondent points is formed. To avoid the problem of instability result from too many unknown parameter, utilize a two-step iterative optimization strategy to solve the distortion parameter, the principle point coordinate and the fundamental matrix, respectively. Utilize the RANSAC robust estimation method to obtain the fundamental matrix and utilize iterative least square optimization method to get the distortion parameter and the principle point coordinate. Proposed method can obtain distortion parameter and the principle point coordinate only by using two images, which is robust to the noise, and can be applied to natural scene image calibration.

关 键 词：计算机视觉 基本矩阵 畸变校正 迭代最小二乘 分步求解 

分 类 号：P237[天文地球—摄影测量与遥感]