A Systematic Scheme For Automatic Airplane Detection From High-Resolution Remote Sensing Images
IMAGE AND VIDEO TECHNOLOGY (PSIVT 2017)(2018)
摘要
Airport and airplane are typical objects in remote sensing research field. However, there are rare methods to detect airport and airplane in a unit system. In this paper, we propose a systematic scheme for airport detection and airplane detection from high-resolution remote sensing images. The airport detection part is mainly based on the parallel line features of runway, containing six main stages: down-sampling, Frequency-Tuned (FT) saliency detection, Line Segment Detector (LSD) line detection, line growing, parallel lines detection and line clustering. The airplane detection part is mainly based on Circle Frequency Filter (CF-filter) and a Fast R-CNN deep learning model. Experimental results on 500 high-resolution remote sensing images acquired more than 95% accuracy, and the average detection time was about 14 s, which proved that the proposed system was effective and efficient.
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关键词
Airplane detection, High-resolution remote sensing images, Circle Frequency Filter, Deep learning
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