Zhao Xinglei, Liang Gang, Liang Ying, Zhao Jianhu, Zhou Fengnian
Appl Opt. 2020 Dec 10;59(35):11019-11026. doi: 10.1364/AO.402973.
Raw full waveforms of green lasers used in airborne LiDAR bathymetry (ALB) are contaminated by background and random noise related to the environment and ALB devices. Traditional thresholding methods have been widely used to reduce background noise in raw full waveforms on the basis of the assumption of constant background noise. However, background noise that is mainly related to background solar radiation and detector dark current changes over time. Thresholding methods perform poorly on the full waveforms with a wide variation range of background noise. A background noise reduction method considering its wide variation is proposed to decrease the background noise by creating trend models. First, each green full waveform is divided into two parts: pulse- and non-pulse-return waveforms. Second, a linear interpolation is conducted on the non-pulse-return waveform to impute the missing noise. Third, a low-pass filter is used to filter the random noise with high frequency in the imputed non-pulse-return waveform and obtain the trend model of background noise of the full waveform. Finally, the derived background noise model is used to decrease the background noise in the pulse-return waveform. The proposed method is applied to decrease the background noise in raw green full waveforms collected by the Optech coastal zone mapping and imaging LiDAR (CZMIL). The mean and standard deviation of residual noise in the CZMIL waveform reduced by the trend model of background noise are -0.03 and 3.5 digitizer counts, respectively. The proposed background noise reduction method is easy to apply and can reduce the background noise to a significantly low level. This method is recommended for preprocessing the raw full waveforms of green lasers collected by Optech CZMIL for ALB.
机载激光雷达测深（ALB）中使用的绿色激光的原始全波形会受到与环境和ALB设备相关的背景及随机噪声的污染。传统的阈值方法基于背景噪声恒定的假设，已被广泛用于降低原始全波形中的背景噪声。然而，主要与背景太阳辐射和探测器暗电流相关的背景噪声会随时间变化。阈值方法在背景噪声变化范围宽的全波形上表现不佳。为了通过创建趋势模型来降低背景噪声，提出了一种考虑其宽变化范围的背景噪声降低方法。首先，将每个绿色全波形分为两部分：脉冲返回波形和非脉冲返回波形。其次，对非脉冲返回波形进行线性插值以估算缺失的噪声。第三，使用低通滤波器对估算出的非脉冲返回波形中的高频随机噪声进行滤波，得到全波形背景噪声的趋势模型。最后，将导出的背景噪声模型用于降低脉冲返回波形中的背景噪声。所提出的方法应用于降低由Optech海岸带测绘与成像激光雷达（CZMIL）采集的原始绿色全波形中的背景噪声。通过背景噪声趋势模型降低后的CZMIL波形中残余噪声的均值和标准差分别为-0.03和3.5数字化器计数。所提出的背景噪声降低方法易于应用，并且可以将背景噪声降低到显著较低的水平。推荐使用此方法对Optech CZMIL采集的用于ALB的绿色激光原始全波形进行预处理。
