Multi-level adaptive photon cloud noise filtering algorithm for different observation time scenes in forest environments

遥感 计算机科学 噪音(视频) 算法 云计算 中值滤波器 环境科学 白天 光子计数 地图集(解剖学) 人工智能 图像处理 地质学 图像(数学) 操作系统 电信 古生物学 大气科学 探测器
作者
Jiapeng Huang,Tingting Xia
出处
期刊:IEEE Transactions on Geoscience and Remote Sensing [Institute of Electrical and Electronics Engineers]
卷期号:: 1-1 被引量:2
标识
DOI:10.1109/tgrs.2023.3347401
摘要

Advanced Topographic Laser Altimeter System (ATLAS) is a new micro-pulse photon-counting laser system that offers unprecedented options for the observation of forest ecosystems. However, the ATLAS system is sensitive to solar background noise, which poses a tremendous challenge to the photon cloud noise filtering for various observation time scenes in a forest environment. This paper presents a multi-level adaptive photon cloud filtering algorithm (MLAPCNF) for different observation time scenes that integrate the improved Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm and the improved localized statistics algorithm. The MLAPCNF algorithm was tested at different observation time scenarios, laser intensities, and forest coverage using the ATLAS dataset for forests located in nine study areas in the USA. The results showed that the MLAPCNF algorithm was effective in identifying noise photons and preserving signal photons in the raw ATLAS data with an R-value of 0.99, and F-value of 0.79 which produced marginally superior results than the other existing filtering methods. The F values of the MLAPCNF algorithm under daytime observation conditions were 0.01-0.03 higher than those under nighttime observation conditions, indicating that the algorithm performed better under daytime observation conditions. Results demonstrated that the proposed method can eliminate the impact of observation time differences in forest environments. Overall, the MLAPCNF algorithm outperforms the other existing filtering techniques at the given test site and is capable of delivering accurate data for estimating forest structural parameters.
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