NDLI: Infrared Small Moving Target Detection via Saliency Histogram and Geometrical Invariability

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Infrared Small Moving Target Detection via Saliency Histogram and Geometrical Invariability

Content Provider	MDPI
Author	Wan, Minjie Ren, Kan Gu, Guohua Zhang, Xiaomin Qian, Weixian Chen, Qian Yu, Shuai
Abstract	In order to detect both bright and dark small moving targets effectively in infrared (IR) video sequences, a saliency histogram and geometrical invariability based method is presented in this paper. First, a saliency map that roughly highlights the salient regions of the original image is obtained by tuning its amplitude spectrum in the frequency domain. Then, a saliency histogram is constructed by means of averaging the accumulated saliency value of each gray level in the map, through which bins corresponding to bright target and dark target are assigned with large values in the histogram. Next, single-frame detection of candidate targets is accomplished by a binarized segmentation using an adaptive threshold, and their centroid coordinates with sub-pixel accuracy are calculated through a connected components labeling method as well as a gray-weighted criterion. Finally, considering the motion characteristics in consecutive frames, an inter-frame false alarm suppression method based on geometrical invariability is developed to improve the precision rate further. Quantitative analyses demonstrate the detecting precision of this proposed approach can be up to 97% and Receiver Operating Characteristic (ROC) curves further verify our method outperforms other state-of-the-arts methods in both detection rate and false alarm rate.
File Size	20640768
File Format	PDF
e-ISSN	20763417
DOI	10.3390/app7060569
Journal	Applied Sciences
Issue Number	6
Volume Number	7
Language	English
Publisher Date	2017-06-01
Access Restriction	Open
Subject Keyword	IR small moving target saliency map saliency histogram geometrical invariability
Content Type	Text
Resource Type	Article

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