Single-photon point cloud parallelogram adaptive denoising algorithm

Yangleijing Li; Guoqing Zhou; Lin Li; Ruixiang Li; Ying Yao

doi:10.1117/12.3041547

11 September 2024 Single-photon point cloud parallelogram adaptive denoising algorithm

Yangleijing Li, Guoqing Zhou, Lin Li, Ruixiang Li, Ying Yao

Proceedings Volume 13253, Fourth International Conference on Signal Image Processing and Communication (ICSIPC 2024); 132530A (2024) https://doi.org/10.1117/12.3041547
Event: 4th International Conference on Signal Image Processing and Communication, 2024, Xi'an, China

Abstract

Newly designed single-photon radar mounted on satellites can gather high-precision three-dimensional data. It is vulnerable to noise, though. This paper offers a parallelogram denoising kernel approach based on multi-feature adaption to solve the irregular background noise and the challenges of signal extraction in steep slope locations. In contrast to conventional circular or elliptical denoising kernels, this approach better matches the properties of single-photon point cloud data. Using a variety of characteristics, including slope and spatial density, it can recognize signals in an adaptive manner. While new radars show excellent accuracy capabilities, noise introduces an error to the measurement. The approach presented in this work solves the signal extraction problem well.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yangleijing Li, Guoqing Zhou, Lin Li, Ruixiang Li, and Ying Yao "Single-photon point cloud parallelogram adaptive denoising algorithm", Proc. SPIE 13253, Fourth International Conference on Signal Image Processing and Communication (ICSIPC 2024), 132530A (11 September 2024); https://doi.org/10.1117/12.3041547

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available