Georgiev Mihail, Bregovic Robert, Gotchev Atanas
IEEE Trans Image Process. 2018 Feb 16. doi: 10.1109/TIP.2018.2807126.
In this work, we deal with the problem of denoising 3D scene range measurements acquired by Time-of-flight (ToF) range sensors and composed in the form of 2D image-like depth maps. We address the specific case of ToF low-sensing environment (LSE). Such environment is set by low-light sensing conditions, low-power hardware requirements, and low-reflectivity scenes. We demonstrate that data captured by a device in such mode can be effectively post-processed in order to reach the same measurement accuracy as if the device was working in normal operating mode. In order to achieve this, we first present an elaborated analysis of noise properties of ToF data sensed in LSE and verify the derived noise models by empirical measurements. Then, we develop a related novel non-local denoising approach working in complex domain and demonstrate its superiority against the state of the art for data acquired by an off-the-shelf ToF device.
在这项工作中，我们处理通过飞行时间（ToF）距离传感器获取并以二维图像式深度图形式组成的三维场景距离测量的去噪问题。我们研究ToF低传感环境（LSE）的特定情况。这种环境由低光照传感条件、低功耗硬件要求和低反射率场景设定。我们证明，在这种模式下由设备捕获的数据可以有效地进行后处理，以达到与设备在正常操作模式下工作时相同的测量精度。为了实现这一点，我们首先对在LSE中感测到的ToF数据的噪声特性进行详细分析，并通过实证测量验证推导的噪声模型。然后，我们开发了一种在复数域工作的相关新颖非局部去噪方法，并证明其相对于现成ToF设备获取的数据的现有技术的优越性。
