飞行时间图像传感器的建模和运动误差分析

Modeling and Motion Error Analysis of a Time-of-Flight Image Sensor

在动态场景中,飞行时间图像传感器的高频多相操作会产生运动模糊,使运动区域内产生错误的三维原始数据,同时增加了电路设计难度。为了减小运动模糊的影响,本文对动态场景下飞行时间图像传感器进行建模。所建模型可以通过简单的参数设置快速完成传感器的参数设定,以仿真动态场景中各条件下的三维图像,从而分析运动误差。本文基于该成像模型,在不同的运动速度和帧频下分析了运动误差对成像质量的影响,探究了动态场景中两种曝光方式之间的成像质量差异,获得了具有高成像质量和低电路设计难度的最优成像指标。采用德州仪器(TI)公司的飞行时间相机对成像模型进行了评估,结果表明,在静态和动态场景中,模型仿真数据与相机实测数据匹配良好。

In dynamic scenes, the high-frequency and multi-phase operation of a time-of-flight image sensor will produce motion blur, causing incorrect three-dimensional original data in the motion area, and increasing the difficulty of circuit design. This paper proposes a time-of-flight image sensor model in a dynamic scene to reduce the impact of motion blur. The model can quickly complete the sensor parameter setting through simple parameter settings, which is used to simulate three-dimensional images in dynamic scenes under various conditions to analyze motion errors. The effect of motion error on imaging quality under different motion speeds and frame rates is analyzed using the imaging model, and the difference in imaging quality between the two exposure modes in dynamic scenes is investigated. Finally, the optimal imaging indicators are obtained, with high imaging quality and low circuit design difficulty. The imaging model is evaluated using a Texas Instruments time-of-flight camera, and the verification results show that the model’s simulation data can effectively match the camera’s measured data in both static and dynamic scenes.