26 October 2013 Low-resolution airplane detection for satellite images using local edge distribution and modulated filtering
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Proceedings Volume 8918, MIPPR 2013: Automatic Target Recognition and Navigation; 891813 (2013) https://doi.org/10.1117/12.2030876
Event: Eighth International Symposium on Multispectral Image Processing and Pattern Recognition, 2013, Wuhan, China
Abstract
Subject to limited resolution for targets in many satellite images, low-resolution airplane detection is still difficult and challenging, which plays an important role in remote sensing. In this paper, we propose a new method to detect lowresolution airplanes in satellite images. First, the image is preprocessed by combing the unsharp contrast enhancement (UCE) filtered image and the original image. Second, the Local Edge Distribution (LED), which is susceptible to objects owning clustered edges, e.g., airplane, is calculated to acquire the target candidate regions while restraining large background area. Then, a multi-scale fused gradient feature image is computed to characterize the shapes of targets instead of the original image to overcome the influence from the self-shadow and different coating colors of airplanes. After that, a designed airplane shape filter with a modulated item is used to detect and locate real targets, in which the modulated item can effectively measure the degree of coincidence between the patch region and the airplane shape. Finally, coordinates of target centers are computed in the filtered image. Experimental results demonstrate that the proposed algorithm is effective and robust for detecting low-resolution airplanes in satellite images under various complex backgrounds.
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Shengxiang Qi, Shengxiang Qi, Jie Ma, Jie Ma, Yadong Zhu, Yadong Zhu, Wei Yu, Wei Yu, Fei Yan, Fei Yan, Jinwen Tian, Jinwen Tian, } "Low-resolution airplane detection for satellite images using local edge distribution and modulated filtering", Proc. SPIE 8918, MIPPR 2013: Automatic Target Recognition and Navigation, 891813 (26 October 2013); doi: 10.1117/12.2030876; https://doi.org/10.1117/12.2030876
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