| A directional-progressive search method for infrared small target detection | |
Zhang XY(张祥越)1,2,3,4 ; Ding QH(丁庆海)5; Luo HB(罗海波)1,3,4; Hui B(惠斌)1,3,4; Chang Z(常铮)1,3,4; Zhang JC(张俊超)1,2,3,4
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| Department | 光电信息技术研究室 |
| Conference Name | 2018 the 3rd Optoelectronics Global Conference (OGC 2018) |
| Conference Date | September 4-7, 2018 |
| Conference Place | Shenzhen, China |
| Author of Source | China International Optoelectronic Conference (CIOEC) ; China International Optoelectronic Expo (CIOE) ; College of Optoelectronic Engineering ; Oung ; Shenzhen University |
| Source Publication | 2018 the 3rd Optoelectronics Global Conference (OGC 2018) |
| Publisher | IEEE |
| Publication Place | New York |
| 2018 | |
| Pages | 180-184 |
| Indexed By | EI |
| EI Accession number | 20185006248763 |
| Contribution Rank | 1 |
| ISBN | 978-1-5386-7397-3 |
| Keyword | infrared image target detection zero-crossing point facet model |
| Abstract | Infrared small target detection plays a key role in infrared precision guidance and infrared early-warning system. It has been a difficult problem for researchers to study on how to detect targets accurately at a long distance as early as possible. Most of the existing algorithms can detect small targets in simple backgrounds, but they would fail on the detection when the background clutters are chaotic and the signal to clutter ratio (SCR) is low. Therefore, we propose a new infrared small target detection method which called a directional-progressive search (DPS) method. Our method derives from a fact that a small target is an isotropic Gaussian distribution at a long distance, while clutters show different characteristics in different directions. Based on this difference, we decompose the original image into first-order sub-images with different directions by using a first-order directional derivative (FODD) filter. Then zero-crossing points are detected in each direction step by step to distinguish small targets and background clutters. After screening progressively, the positions where existing zero-crossing points in every sub-image can be confirmed as targets. Experimental results show that our method acquires higher detection rates and lower false alarm rates compared with other methods. At the same time, our method can still keep better performance under various complex backgrounds. The robustness of our method is strong. |
| Language | 英语 |
| Document Type | 会议论文 |
| Identifier | http://ir.sia.cn/handle/173321/23786 |
| Collection | 光电信息技术研究室 |
| Corresponding Author | Zhang XY(张祥越) |
| Affiliation | 1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 2.University of Chinese Academy of Sciences, Beijing 100049, China 3.Key Laboratory of Opto-Electronic Information Processing, CAS, Shenyang 110016, China 4.Key Lab of Image Understanding and Computer Vision, Liaoning Province, Shenyang 110016, China 5.Space Star Technology Co. Ltd, Beijing 100086, China |
| Recommended Citation GB/T 7714 | Zhang XY,Ding QH,Luo HB,et al. A directional-progressive search method for infrared small target detection[C]//China International Optoelectronic Conference (CIOEC), China International Optoelectronic Expo (CIOE), College of Optoelectronic Engineering, Oung, Shenzhen University. New York:IEEE,2018:180-184. |
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| File Name/Size | DocType | Version | Access | License | ||
| A directional-progre（3414KB） | 会议论文 | 开放获取 | CC BY-NC-SA | View Download | ||
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