Laser Target Localization Based on Symmetric Wavelet Denoising and Asymmetric Gauss Fitting

Junling, 孙俊灵 Sun; Guangmin, 孙光民 Sun; Pengge, 马鹏阁 Ma; Tao, 董涛 Dong; Yi, 羊毅 Yang

doi:10.3788/cjl201744.0604001

Cited by 5 publications

(1 citation statement)

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“…The remote sensing technology supports for large-scale forest resource survey and management, which can help to timely understand the dynamic changes of vegetation [16]. Compared with optical remote sensing technology, 3D lidar has higher measurement accuracy and faster data processing speed [17], [18]. Ferraz, A. et al [19] apply a statistical approach based on the Mean-Shift algorithm to decompose the ALS point cloud into 3D segments corresponding to individual vegetation features.…”

Section: Introductionmentioning

confidence: 99%

Passive Measurement Method of Tree Height and Crown Diameter Using a Smartphone

Xinmei

Yang

2020

IEEE Access

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The tree height and crown diameter are important measurement attributes in forest resource survey and management. Hence, we propose a passive measurement method of tree height and crown diameter based on monocular camera of a smartphone. First, we use an feature-adaptive Mean-Shift algorithm to segment the image and extract tree's contour. Furthermore, an adaptive feature coordinate system is established to help study the conversion relationship of the coordinate systems. It has been proved that for the image points with the same abscissa pixels, their ordinate pixels have a linear relationship with its actual imaging angles. A depth extraction model is built according to this principle. Then, we obtain the rotation and translation matrix and established tree height and crown diameter models according to the mapping transformation relationship of coordinates. Experimental results reveal significant correlation between calculated and truth values. The RMSE is 0.267 m (rRMS=2.482%) for tree height and 0.209 m (rRMS=5.631%) for crown diameter. The relative errors of tree heights are less than 5.76% (MRE=2.159%); for crown diameter, the relative errors are less than 9.73% (MRE=4.95%). Overall, the accuracy of this method falls within the requirements of the continuous inventory of Chinese national forest resources. INDEX TERMS Tree height, crown diameter, monocular vision, passive Measurement, depth extraction model.

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Section: Introductionmentioning

confidence: 99%