Infrared dim small target detection based on visual saliency and local entropy

2022 ◽  
Vol 15 (0) ◽  
pp. 1-9
Author(s):  
ZHAO Peng-peng ◽  
◽  
◽  
LI Shu-zhong ◽  
LI Xun ◽  
...  
Keyword(s):  
Target Detection ◽  
Visual Saliency ◽  
Small Target ◽  
Local Entropy ◽  
Small Target Detection

Infrared small target detection based on modified local entropy and EMD

2010 ◽  
Vol 8 (1) ◽  
pp. 24-28 ◽  
Author(s):  
邓鹤 He Deng ◽  
刘建国 Jianguo Liu ◽  
陈忠 Zhong Chen
Keyword(s):  
Target Detection ◽  
Small Target ◽  
Local Entropy ◽  
Small Target Detection ◽  
Infrared Small Target

Small Target Detection Based on Visual Saliency Improved by Spatial Distance

2015 ◽  
Vol 35 (7) ◽  
pp. 0715004 ◽  
Author(s):  
杨林娜 Yang Linna ◽  
安玮 An Wei ◽  
林再平 Lin Zaiping ◽  
李安冬 Li Andong
Keyword(s):  
Target Detection ◽  
Visual Saliency ◽  
Spatial Distance ◽  
Small Target ◽  
Small Target Detection

scholarly journals Infrared Small Target Detection Through Multiple Feature Analysis Based on Visual Saliency

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 38996-39004 ◽  
Author(s):  
Yuwen Chen ◽  
Bin Song ◽  
Xiaojiang Du ◽  
Mohsen Guizani
Keyword(s):  
Target Detection ◽  
Visual Saliency ◽  
Feature Analysis ◽  
Small Target ◽  
Small Target Detection ◽  
Multiple Feature ◽  
Infrared Small Target

scholarly journals Infrared Small Target Detection Method Combined with Bilateral Filter and Local Entropy

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Zhonghua Wang ◽  
Siwei Duan ◽  
Chengli Sun
Keyword(s):  
False Alarm ◽  
False Alarm Rate ◽  
Target Detection ◽  
Bilateral Filter ◽  
Background Suppression ◽  
Small Target ◽  
Local Entropy ◽  
Edge Preserving ◽  
Small Target Detection ◽  
Infrared Small Target

According to the larger false alarm rate resulted from fluctuant clutter, a novel method combined with bilateral filter and local entropy is proposed for infrared small target detection in this paper. Firstly, the original image is respectively processed by bilateral filter and local entropy, and then the two processed images are fused by point product to generate the background suppression map. Secondly, the guided filter is used to further suppress the background and enhance the small target in the map. Thirdly, the small target is detected by the adaptive threshold in the filtered map. The theoretical analyses and experimental results show that the proposed method not only effectively suppresses the clutter background, depending on the edge preserving and denoising characteristics of bilateral filtering, but also effectively highlights the small target, relying on the sensitivity of local entropy to the abrupt gray region. Compared with other methods, it is demonstrated that the proposed method owns lower false alarm rate and higher detection rate.

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