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Proceedings Paper

3D target detection of Geiger mode APD array lidar image
Author(s): Tianming Zhao; Jinwen Tian; Hang Liu; Peng Jiang
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Paper Abstract

The Geiger mode Avalanche Photo Diode (APD) array lidar is a non-scanning lidar, which has a small volume, fast imaging speed and high sensitivity. In the paper, the 3D target detection of Geiger mode APD array lidar image is studied. Geiger mode APD array lidar has great noise in the process of imaging due to its imaging characteristics. The paper analyzes its noise characteristics and decomposes the noise into four parts: environment noise, loss noise, internal noise and crosstalk noise. According to the noise characteristics, the paper simulated the Geiger-mode APD array lidar imaging. And based on this, the target detection algorithm was studied. The paper proposes a filtering method based on the KNN classification and combine an improved loop filtering algorithm to preprocess the image. And then an adaptive superposition algorithm is proposed to fuse the preprocessed multi-frame image. Testing the target detection algorithm on five image data captured by the Geiger mode APD array lidar, the medium-scale and small-scale targets can be detected in 20 frames. The largescale targets can be detected in 50 frames, and long-distance targets can be detected in 100 frames.

Paper Details

Date Published: 14 February 2020
PDF: 7 pages
Proc. SPIE 11432, MIPPR 2019: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 114321K (14 February 2020); doi: 10.1117/12.2541902
Show Author Affiliations
Tianming Zhao, Huazhong Univ. of Science and Technology (China)
Jinwen Tian, Huazhong Univ. of Science and Technology (China)
Hang Liu, Huazhong Univ. of Science and Technology (China)
Peng Jiang, Institute of Mechanical and Electrical Engineering (China)


Published in SPIE Proceedings Vol. 11432:
MIPPR 2019: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications
Zhiguo Cao; Jie Ma; Zhong Chen; Yu Shi, Editor(s)

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