Detection of building area with complex background by night light remote sensing
投稿时间:2020-04-05  修订日期:2020-10-26  download
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李海 华中科技大学 人工智能与自动化学院 多谱信息处理技术国家级重点实验室湖北武汉 430074 430074
李洋 上海交通大学 机器人研究所上海 200240 
左峥嵘 华中科技大学 人工智能与自动化学院 多谱信息处理技术国家级重点实验室湖北武汉 430074 430074
Abstract:A new single-stage deep convolution detection network is proposed to solve the complex background problem of night light remote sensing. Firstly, a classification network is designed by extracting high-dimensional features and then selecting features, and the influence of different channel number networks of noise reduction is studied. A prior box matching of gray-scale energy is proposed, inputting a low-noise and high-quality matching box into SSD detection network, and the idea of integral diagram is used to simplify the calculation. By adding sequential connection and dense connection to improve the global semantic module, the cross layered information interaction of the network is introduced, and its attention map comprehensively considers the high and low receptive fields to effectively distinguish small targets and background noise. Experimental results of the night light remote sensing data set show that the designed network has advantages over the rest single-stage network, which has a better detection effect of the building area under the complex background.
keywords:pattern recognition and intelligent system,night light remote sensing,depth convolution network,building area detection,complex background
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Copyright:《Journal of Infrared And Millimeter Waves》