Dim small targets detection based on self-adaptive caliber temporal-spatial filtering |
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Institution: | 1. Department of Arts and Sciences, Chengdu College of University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China;2. School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China;3. School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, Shaanxi 710049, PR China |
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Abstract: | To boost the detect ability of dim small targets, this paper began by using improved anisotropy for background prediction (IABP), followed by target enhancement by improved high-order cumulates (HQS). Finally, on the basis of image pre-processing, to address the problem of missed and wrong detection caused by fixed caliber of traditional pipeline filtering, this paper used targets’ multi-frame movement correlation in the time-space domain, combined with the scale-space theory, to propose a temporal-spatial filtering algorithm which allows the caliber to make self-adaptive changes according to the changes of the targets’ scale, effectively solving the detection-related issues brought by unchanged caliber and decreased/increased size of the targets. Experiments showed that the improved anisotropic background predication could be loyal to the true background of the original image to the maximum extent, presenting a superior overall performance to other background prediction methods; the improved HQS significantly increased the signal-noise ratio of images; when the signal-noise ratio was lower than 2.6 dB, this detection algorithm could effectively eliminate noise and detect targets. For the algorithm, the lowest signal-to-noise ratio of the detectable target is 0.37. |
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Keywords: | Dim small target detection Background suppression Improved anisotropy for background prediction Improved high-order accumulation Self-adaptive caliber Time-space domain |
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