Infrared small-target detection based on multi-directional multi-scale high-boost response
| Autor: | Lingbing Peng, Tian Pu, Tianfang Zhang, Zhenming Peng, Suqi Huang, Yuxiao Lv, Yunchang Zheng, Yuhan Liu |
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| Rok vydání: | 2019 |
| Předmět: |
Computer science
business.industry Interface (computing) Pattern recognition Cloud computing 02 engineering and technology Interference (wave propagation) 01 natural sciences Atomic and Molecular Physics and Optics 010309 optics Search engine 020210 optoelectronics & photonics 0103 physical sciences Human visual system model 0202 electrical engineering electronic engineering information engineering Segmentation Noise (video) Artificial intelligence Scale (map) business |
| Zdroj: | Optical Review. 26:568-582 |
| ISSN: | 1349-9432 1340-6000 |
| Popis: | As of late, infrared (IR) small-target detection technology is broadly utilized in low-altitude monitoring frameworks, target-tracking frameworks, precise guidance frameworks and forest fire prevention frameworks. In this paper, we propose an infrared small-target detection strategy based on multi-directional multi-scale high-boost response (MDMSHB). First, an eight-direction filtering template is proposed, which can consider the directional information of the image and significantly suppress heterogeneous background such as cloud, linear interference and interface like ocean–sky background. Then, a map based on multi-directional multi-scale high-boost response (MDMSHB map) is calculated. Finally, a straightforward threshold segmentation technique is utilized to get the detection result. The simulation results comparing this method with the four state-of-the-art strategies in six sequences demonstrate that the proposed strategy can adequately suppress heterogeneous background and arbitrary noise. The approach can improve detection rate and reduce false alert rate as well. |
| Databáze: | OpenAIRE |
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