Dr. Haiying Zhang Profile

Dr. Haiying Zhang

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Proceedings Article | 10 April 2018 Paper

A speeded-up saliency region-based contrast detection method for small targets

Zhengjie Li, Haiying Zhang, Jiaojiao Bai, Zhongjun Zhou, Huihuang Zheng

Proceedings Volume 10615, 1061506 (2018) https://doi.org/10.1117/12.2302488

KEYWORDS: Target detection, Detection and tracking algorithms, Image compression, Infrared radiation, Image analysis, Infrared detectors, Image segmentation

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To cope with the rapid development of the real applications for infrared small targets, the researchers have tried their best to pursue more robust detection methods. At present, the contrast measure-based method has become a promising research branch. Following the framework, in this paper, a speeded-up contrast measure scheme is proposed based on the saliency detection and density clustering. First, the saliency region is segmented by saliency detection method, and then, the Multi-scale contrast calculation is carried out on it instead of traversing the whole image. Second, the target with a certain “integrity” property in spatial is exploited to distinguish the target from the isolated noises by density clustering. Finally, the targets are detected by a self-adaptation threshold. Compared with time-consuming MPCM (Multiscale Patch Contrast Map), the time cost of the speeded-up version is within a few seconds. Additional, due to the use of “clustering segmentation”, the false alarm caused by heavy noises can be restrained to a lower level. The experiments show that our method has a satisfied FASR (False alarm suppression ratio) and real-time performance compared with the state-of-art algorithms no matter in cloudy sky or sea-sky background.

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