Paper
5 October 2017 Airport object extraction based on visual attention mechanism and parallel line detection
Author Affiliations +
Proceedings Volume 10432, Target and Background Signatures III; 104320S (2017) https://doi.org/10.1117/12.2280449
Event: SPIE Security + Defence, 2017, Warsaw, Poland
Abstract
Target extraction is one of the important aspects in remote sensing image analysis and processing, which has wide applications in images compression, target tracking, target recognition and change detection. Among different targets, airport has attracted more and more attention due to its significance in military and civilian. In this paper, we propose a novel and reliable airport object extraction model combining visual attention mechanism and parallel line detection algorithm. First, a novel saliency analysis model for remote sensing images with airport region is proposed to complete statistical saliency feature analysis. The proposed model can precisely extract the most salient region and preferably suppress the background interference. Then, the prior geometric knowledge is analyzed and airport runways contained two parallel lines with similar length are detected efficiently. Finally, we use the improved Otsu threshold segmentation method to segment and extract the airport regions from the salient map of remote sensing images. The experimental results demonstrate that the proposed model outperforms existing saliency analysis models and shows good performance in the detection of the airport.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jing Lv, Wen Lv, and Libao Zhang "Airport object extraction based on visual attention mechanism and parallel line detection", Proc. SPIE 10432, Target and Background Signatures III, 104320S (5 October 2017); https://doi.org/10.1117/12.2280449
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KEYWORDS
Remote sensing

Image segmentation

Performance modeling

Visualization

RGB color model

Statistical analysis

Visual process modeling

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