Fast reflectance spectral profile reconstruction method for full-waveform hyperspectral LiDAR
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摘要: 全波形高光谱激光雷达(HSL)在获得高精度、高分辨率的空间数据的同时,还能获得目标的光谱信息,可为不同研究和应用领域提供有效和多维的数据。然而,HSL不同波段发射信号强度存在差异,会导致相应回波信号的差异,难以直接利用回波信号来重建目标在不同波段下准确的光学特性(目标的反射率光谱分布曲线)。以往研究通常利用标准漫反射白板法来获取目标的反射率光谱曲线(标准参照板法)。但在某些复杂的检测环境中白板易受污染,且激光器的发射能量会因环境和设备状态的变化出现波动,进而影响计算精度。因此,从全波形信号本身直接提取信息用于反射率光谱曲线重建是一种快捷的途径。基于此,我们提出一种基于 HSL 全波形数据的回波强度校正方法,用于快速生成目标的反射率光谱曲线。首先,通过理论分析,证明回波与发射波在形状上的相似性。然后,对HSL全波形的发射信号和回波信号进行偏正态高斯函数拟合,计算各波段在理想情况下标准漫反射白板的发射信号与回波信号峰值比值(归一化因子)。最后,通过结合标准漫反射白板的归一化因子与目标的归一化因子来构建目标的反射率光谱分布曲线。为验证本文方法的有效性,我们将其与基于标准漫反射板计算的反射率光谱曲线进行了对比实验,并进行木叶分离和目标分类实验以评估其适用性。实验结果表明:(1)利用发射信号校正回波强度,可以获得与标准参照板法相似的反射率光谱曲线。并且在不同温度及光照条件下均表现出良好的稳定性;与标准漫反射白板法相比,该方法有效克服了激光器发射能量波动的影响,尤其在HSL长时间工作条件下,显著提升了反射率光谱曲线的测量精度和一致性。(2)在实际应用中,基于本文方法获得的目标反射率光谱曲线能够快速实现木叶分离,且对果树目标分类准确率超过90%。本文方法简化了全波形高光谱激光雷达的回波强度校正流程,可在数据采集过程中实时快速重建目标高光谱信息。Abstract: Hyperspectral LiDAR (HSL) can obtain high precision and resolution spatial data along with the spectral information of the target, which can provide effective and multidimensional data for various research and application fields. However, differences in transmitting signal intensities of HSL at various wavelengths lead to variations in corresponding echo intensities, making it challenging to directly reconstruct accurate optical characteristics (reflectance spectral profile) of the target with echo intensities. To obtain the target reflectance spectral profile, a common solution is to correct the echo intensity (standard reference correction method) using standard diffuse reflectance whiteboards. However, in complex detection environments, whiteboards are susceptible to contamination, and the transmitting intensity of the laser may fluctuate due to changes in the environment and equipment conditions, which may potentially impact the calculation accuracy. The direct transmission of information from the full-waveform signals to the reconstruction of the reflectance spectral profiles is a more efficient approach. Therefore, we propose an echo intensity correction method based on HSL full-waveform data for the rapid generation of reflectance spectral profiles of targets. The initial step is to conduct a theoretical analysis that illustrates the similarity between the echo signals and the transmitting signals in terms of their waveforms. A skew-normal Gaussian function is then employed to fit the transmitting and echo signals of the HSL full waveform. Thereafter, the transmit-to-echo signal peak ratios (normalization factors) of the standard diffuse reflectance whiteboard at different wavelengths are calculated under ideal conditions. Finally, the reflectance spectral profile of the target is constructed by combining the normalization factor of the standard diffuse reflectance whiteboard with that of the target. To verify the effectiveness of the proposed method, we conducted experiments to compare the reflectance spectral profiles calculated using the standard reference correction method. Moreover, we performed wood–leaf separation and target classification experiments to assess its reliability and usability. The experimental results reveal the following: (1) the reconstructed reflectance spectral profiles of the target can be obtained by correcting the echo intensity with the transmitting signals, which is similar to that obtained by the standard reference correction method. Moreover, it demonstrates excellent stability under various temperatures and lighting conditions. Compared with the standard reference correction method, this approach effectively overcomes the influence of laser emission energy fluctuations, thereby considerably improving the measurement accuracy and consistency of reflectance spectral curves, especially under prolonged HSL operation conditions. (2) The wood–leaf separation and the multiple target classification can be conducted using the reconstructed target reflectance spectral profiles, with a classification accuracy of over 90%. Overall, the proposed method simplifies the correction of echo intensity for full-waveform HSL, which is suitable for the rapid reconstruction of target hyperspectral information during data acquisition.
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表 1 HSL 的系统参数
Table 1. System parameters of HSL
参数 数值 光谱范围 550~ 1050 nm光谱分辨率
输出效率
光束发散角
采样速率5 nm
>40%
~0.35 mrad
5 GHz/s表 2 实验样本
Table 2. Experimental sample
样本 名称 扫描时间 点数 图片 1 标准漫反射参照板 9 s 3 2 绿萝
(Epipremnum aureum)9 s 3 3 铁板
(iron plate)9 s 3 4 纸板(cardboard) 9 s 3 5 发财树
(Pachira macrocarpa)1.5 h 1810 6 柠檬树
(Citrus limon)2.5 h 3016 -
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