A new waveform decomposition method for multispectral LiDAR

Song, Shalei; Wang, Binhui; Gong, Wei; Chen, Zhenwei; Lin, Xin; Sun, Jiayue; Shi, Shuo

doi:10.1016/j.isprsjprs.2019.01.014

Cited by 39 publications

(15 citation statements)

References 30 publications

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“…To investigate the feasibility and accuracy of the color restoration that extracts color information from multispectral full-waveform data, the experimental datasets were utilized as described in Section 3.2. Since the waveform data measured by the FWMSL system is slightly asymmetrical with trailing, the measured data was fitted using both the proposed multispectral lognormal function and the Gaussian function [14] in order to verify whether the former can improve the color restoration accuracy compared to the latter. In addition, the intensity can be expressed as amplitude or integral area as mentioned in Section 3.1.1.…”

Section: Resultsmentioning

confidence: 99%

“…We used four solid-state lasers at 556, 670, 700 and 780 nm with full-waveform recording of the receiving channels for monitoring the growth and nutritional status of vegetation. The previous MSL was effective in capturing abundant biochemical information of vegetation [15] and had increased waveform decomposition accuracy [14]. Given its significant improvement in vegetation detection, we found that directly synthesizing the true color of targets based on these selected laser bands remains difficult due to the lack of a B band laser source, which results in low visualization and limits the capability to render the true surface color of the target.…”

Section: Fwmsl Systemmentioning

confidence: 99%

“…In recent years, the development of multispectral LiDAR (MSL) or even hyperspectral LiDAR (HSL) systems [14][15][16][17][18] have effectively increased the receiving channels of full waveform data for interest wavelengths. These new MSL/HSL systems often utilize a supercontinuum laser source which produces broadband light almost covering the whole visible light band, including red (R), green (G) and blue (B) bands [19].…”

Section: Introductionmentioning

confidence: 99%

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Color Restoration for Full-Waveform Multispectral LiDAR Data

et al. 2020

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The current full-waveform data at a single wavelength can mainly retrieve the geometric attributes of targets along the light path by detecting waveform components, resulting in the lack of spectral or color attribute information. This kind of device relies on a digital camera for acquiring the color information, however, which is inevitably limited by the lighting conditions and geometric registration errors. With the development of multispectral light detection and ranging (LiDAR) or even hyperspectral LiDAR that often utilize a supercontinuum laser source covering the whole visible light band, including red, green and blue bands, the simultaneous acquisition of color and spatial information becomes possible and makes passive imaging data no longer necessary. In this study, we propose a color restoration method for a full-waveform multispectral LiDAR (FWMSL) system. Additionally, we develop a multispectral lognormal function to fit the tailing echoes measured by FWMSL further accurately. Experimental data from our FWMSL system are used to evaluate the performance of the proposed method. The relative standard deviation, correlation coefficient (R 2 ) and color difference (∆E) metrics suggest that the color restoration for the full-waveform multispectral data is feasible. (Figure 1b), the RGB bands, namely, 434.5-474.5, 517-537 and 612-644 nm, in the visible spectral portion were selected for the receiving channels of color information. In addition, the photo multiplier tube (PMT) selected as the detector should be more suitable for detecting laser echoes in visible bands than the avalanche photodiode especially in the relatively low-energy B band since PMT has higher quantum efficiency and gain. Moreover, both the transmitted pulse and receiving echo at RGB bands are full-waveform recorded so that the receiving echoes can be calibrated with the transmitted pulses to eliminate errors caused by laser output energy instability. The waveforms of the three receiving channels were digitized in a 12-bit analog to digital converter (SP Devices, ADQ412), with a 1.8 GHz sampling rate. The length of each active signal is set to 20 samples based on the laser pulse width of 2 ns and sampling rate, thus greatly reducing the amount of data. Remote Sens. 2019, 11, x FOR PEER REVIEW 3 of 19 photo multiplier tube (PMT) selected as the detector should be more suitable for detecting laser 96 echoes in visible bands than the avalanche photodiode especially in the relatively low-energy B band 97 since PMT has higher quantum efficiency and gain. Moreover, both the transmitted pulse and 98 receiving echo at RGB bands are full-waveform recorded so that the receiving echoes can be 99 calibrated with the transmitted pulses to eliminate errors caused by laser output energy instability. 100The waveforms of the three receiving channels were digitized in a 12-bit analog to digital converter 101 (SP Devices, ADQ412), with a 1.8 GHz sampling rate. The length of each active signal is set to 20 102 samples based on the laser pulse width of 2 ns a...

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Section: Resultsmentioning

confidence: 99%

Section: Fwmsl Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Color Restoration for Full-Waveform Multispectral LiDAR Data

et al. 2020

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“…Similar to the Gaussian decomposition method, the peak and inflection points can be combined in the preprocessing stage to estimate the number of echo components and their initial parameters (Song et al 2019, Wang et al 2015. The translation factor m  in the range direction can be initialized…”

Section: Multispectral Waveform Decompositionmentioning

confidence: 99%

“…Moreover, most of these waveform decomposition methods operate at a single laser wavelength and cannot be applied well to multispectral LiDAR (MSL) or hyperspectral LiDAR (HSL). MSL and HSL have been proposed to simultaneously collect the spectral and geometric attributes with multiple transmitting laser wavelengths in recent years, widely adopted in vegetation detection and land cover mapping (Wei et al 2012, Guerrero-Rascado et al 2014, Song et al 2019, Hakala et al 2012, Scaioni et al 2018.…”

Section: Introductionmentioning

confidence: 99%

High-Precision Ranging Based on Multispectral Full-Waveform Lidar

Wang

Song

Gong

et al. 2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Full-waveform light detection and ranging (LiDAR) has become a well-established technique for remote sensing of surface topography and target characterization, offering numerous opportunities in investigation and interpretation of the structural diversity of surface coverage. However, most prevailing waveform decomposition methods employ the Gaussian function or some other probability distributions to model LiDAR waveforms of specific shapes, which cannot be universally used. Moreover, most of these waveform decomposition methods operate at a single laser wavelength and cannot be applied well to multispectral LiDAR (MSL) or hyperspectral LiDAR (HSL), which can simultaneously collect the spectral and geometric attributes with multiple transmitting laser wavelengths. In this paper, we propose a new multispectral B-spline waveform decomposition model to achieve high precision multi-target ranging. Considering both the spatial consistency of each channel and the irregular shape of the received waveform, LiDAR waveforms are modelled by B-splines rather than any other specific probability distribution. Thus, the proposed method can be extended to other FWMSL data benefiting from the flexibility of B-splines on fitting arbitrary curves. Both simulated MSL echoes and a measured dataset from a FWMSL system with three wavelengths of 556, 670, and 780 nm were used in this study. Compared with two single wavelength waveform decomposition models and a multispectral waveform decomposition model based on Gaussian function, the proposed method has excellent robustness for processing different shapes of waveforms and can improve ranging accuracy significantly for irregular waveforms.

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