一种基于密度的多层地形适应噪声去除方法,用于ICESat-2光子计数数据
Longyu Wang1, Xuqing Zhang1, Ying Zhang1
1College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China.
Sensors (Basel, Switzerland)
|December 23, 2023
概括
一种新的方法,MTANR,有效地消除了ICESat-2光子数据中的噪声,改善了用于植被分析的信号提取. 这种适应地形的方法提高了准确性,特别是在具有挑战性的斜坡和各种地形上.
科学领域:
- 地理空间分析是什么?
- 遥感技术是远程传感技术.
- 在光子点云处理过程中,
背景情况:
- ICESat-2光子点云对于应用至关重要,但含有阻碍信号提取的噪音.
- 在信号附近的边缘噪声在数据处理中构成了重大挑战.
- 准确的信号检测对于了解植被覆盖面和地形特征至关重要.
研究的目的:
- 为ICESat-2数据提出一种基于密度的多层地形适应噪声消除方法 (MTANR).
- 为了提高信号光子检测的准确性,特别是在不同斜率的植被地区.
- 开发一个强大的消除噪声策略,有效地保护信号光子.
主要方法:
- 实施了基于光子分布的粗到细噪声识别策略.
- 使用基于直方图的连续无声化来减少最初的噪音.
- 使用可旋转的圆和Otsu的方法与OPTICS用于自适应的稀疏和边缘噪声去除.
- 使用高精度空中LiDAR数据验证了该方法.
主要成果:
- 在四个测试区域中,MTANR在信号光子识别方面取得了高F1得分 (0.95340.9857).
- 超越了现有的方法,如DRAGANN,LDS和基于水平圆的OPTICS.
- 在复杂的场景中表现出卓越的表现,包括的斜坡,急剧的地形变化和不均的植被.
结论:
- MTANR方法在处理ICESat-2光子点云方面取得了重大进展.
- 它有效地消除各种类型的噪音,同时保留关键的信号数据.
- MTANR提供了一个强大的解决方案,用于从卫星数据中准确地分析植被和地形.
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