1 November 2016 Infrared moving small target detection based on saliency extraction and image sparse representation
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Proceedings Volume 10157, Infrared Technology and Applications, and Robot Sensing and Advanced Control; 1015734 (2016) https://doi.org/10.1117/12.2247309
Event: International Symposium on Optoelectronic Technology and Application 2016, 2016, Beijing, China
Abstract
Moving small target detection in infrared image is a crucial technique of infrared search and tracking system. This paper present a novel small target detection technique based on frequency-domain saliency extraction and image sparse representation. First, we exploit the features of Fourier spectrum image and magnitude spectrum of Fourier transform to make a rough extract of saliency regions and use a threshold segmentation system to classify the regions which look salient from the background, which gives us a binary image as result. Second, a new patch-image model and over-complete dictionary were introduced to the detection system, then the infrared small target detection was converted into a problem solving and optimization process of patch-image information reconstruction based on sparse representation. More specifically, the test image and binary image can be decomposed into some image patches follow certain rules. We select the target potential area according to the binary patch-image which contains salient region information, then exploit the over-complete infrared small target dictionary to reconstruct the test image blocks which may contain targets. The coefficients of target image patch satisfy sparse features. Finally, for image sequence, Euclidean distance was used to reduce false alarm ratio and increase the detection accuracy of moving small targets in infrared images due to the target position correlation between frames.
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Xiaomin Zhang, Xiaomin Zhang, Kan Ren, Kan Ren, Jin Gao, Jin Gao, Chaowei Li, Chaowei Li, Guohua Gu, Guohua Gu, Minjie Wan, Minjie Wan, } "Infrared moving small target detection based on saliency extraction and image sparse representation", Proc. SPIE 10157, Infrared Technology and Applications, and Robot Sensing and Advanced Control, 1015734 (1 November 2016); doi: 10.1117/12.2247309; https://doi.org/10.1117/12.2247309
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