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An object-based analysis filtering algorithm for airborne laser scanning
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DOI：10.1080/01431161.2012.699694.png)
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Abstract
En 中文
Ground filtering is a key process to derive digital terrain models from airborne laser scanning data. Although many methods have been developed to tackle the filtering problem, it has not been fully solved so far. Current algorithms mainly focus on neighbourhood-based or directional filtering approaches. A new object-based analysis (OBA) method is proposed in this article. First, a grid index algorithm accelerates access to unorganized cloud points. Then, a segmentation algorithm is deployed based on the index, and objects are obtained. A filtering logic that utilizes the objects' characteristics is designed. Following this, the performance of the method is comprehensively tested using publicly available International Society for Photogrammetry and Remote Sensing (ISPRS) test data sets for nine urban and six rural regions, and the results are compared to those of eight other algorithms. The OBA method implemented in this article reveals good results without scene-wise optimization of the parameters, and it ranks third or fourth in most of the cases.
Keywords:
LIDAR DATA
IMAGE SEGMENTATION
EXTRACTION
FRAMEWORK
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