Tree Depth Image Generation Algorithm Based on Short Video Images

Hong Yang; Aijun Xu

doi:10.3788/LOP57.161011

Laser & Optoelectronics Progress, Volume. 57, Issue 16, 161011(2020)

Tree Depth Image Generation Algorithm Based on Short Video Images

Hong Yang^1,2 and Aijun Xu^1,2,3、*

Author Affiliations

¹School of Information Engineering, Zhejiang A & F University, Hangzhou, Zhejiang 311300, China;

²Zhejiang Provincial Key Laboratory of Forestry Intelligent Monitoring and Information Technology, Zhejiang A & F University, Hangzhou, Zhejiang 311300, China;

³Key Laboratory of State Forestry and Grassland Administration on Forestry Sensing Technology and Intelligent Engineering, Zhejiang A & F University, Hangzhou, Zhejiang 311300, China;

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Figures & Tables(12)

Fig. 1. Schematic of proposed algorithm

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Fig. 2. s-t network

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Fig. 3. Segmentation results of tree image. (a) Before segmentation; (b) after segmentation

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Fig. 4. Tree feature points

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Fig. 5. D-U radial distortion model

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Fig. 6. Schematic of plane scanning method

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Fig. 7. Schematic of camera motion trajectory. (a) Reference frame; (b) stacking of each frame; (c) details

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Fig. 8. Segmentation of tree image and extraction of feature points. (a) Reference frame; (b) feature points before segmentation; (c) feature points after segmentation

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Fig. 9. Focal length values after bundle adjustment withdifferent feature points

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Fig. 10. Depth images generated by different algorithms. (a) Input images; (b) depth images generated by Ref. [23]; (c) depth images generated by Ref. [24]; (d) depth images generated by proposed algorithm

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Table 1. Mean standard deviation of focal length of different feature point beam algorithms
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Table 1. Mean standard deviation of focal length of different feature point beam algorithms
Algorithm Mean standarddeviation
Corner point 295.33
Sub-pixel corner point 128.92
Corner point after segmentation 91.49
Sub-pixel corner point after segmentation 29.11

Table 2. Objective evaluation index of depth images
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Table 2. Objective evaluation index of depth images
Algorithm Ref.[23] Ref. [24] Proposed
Rel 0.42 0.35 0.34
Sq Rel 38.22 25.35 23.02
RMS 66.87 63.50 60.58
SSIM 0.85 0.73 0.80