Infrared small-target detection based on multi-directional multi-scale high-boost response

2019 ◽  
Vol 26 (6) ◽  
pp. 568-582 ◽  
Author(s):  
Lingbing Peng ◽  
Tianfang Zhang ◽  
Suqi Huang ◽  
Tian Pu ◽  
Yuhan Liu ◽  
...  
Keyword(s):  
Target Detection ◽  
Small Target ◽  
Small Target Detection ◽  
Multi Scale ◽  
Infrared Small Target

scholarly journals Multi-Scale Infrared Small Target Detection Method via Precise Feature Matching and Scale Selection Strategy

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 48660-48672
Author(s):  
Zujing Yan ◽  
Yunhong Xin ◽  
Ruiheng Su ◽  
Xiaojie Liang ◽  
He Wang
Keyword(s):  
Target Detection ◽  
Feature Matching ◽  
Detection Method ◽  
Selection Strategy ◽  
Small Target ◽  
Scale Selection ◽  
Small Target Detection ◽  
Multi Scale ◽  
Infrared Small Target

scholarly journals Infrared small target detection method based on multi-scale feature fusion

2021 ◽  
Vol 2024 (1) ◽  
pp. 012012
Author(s):  
Fang Wang ◽  
Chuanqiang Li ◽  
Bo Wu ◽  
Kun Yu ◽  
Chan Jin
Keyword(s):  
Target Detection ◽  
Detection Method ◽  
Feature Fusion ◽  
Small Target ◽  
Scale Feature ◽  
Small Target Detection ◽  
Multi Scale ◽  
Infrared Small Target

scholarly journals Infrared small target detection based on region proposal and CNN classifier

2021 ◽  
Author(s):  
Mingming Fan ◽  
Shaoqing Tian ◽  
Kai Liu ◽  
Jiaxin Zhao ◽  
Yunsong Li
Keyword(s):  
Neural Network ◽  
False Alarm ◽  
False Alarm Rate ◽  
Target Detection ◽  
Detection Rate ◽  
Corner Detection ◽  
Small Target ◽  
Small Target Detection ◽  
Potential Target ◽  
Infrared Small Target

AbstractInfrared small target detection has been a challenging task due to the weak radiation intensity of targets and the complexity of the background. Traditional methods using hand-designed features are usually effective for specific background and have the problems of low detection rate and high false alarm rate in complex infrared scene. In order to fully exploit the features of infrared image, this paper proposes an infrared small target detection method based on region proposal and convolution neural network. Firstly, the small target intensity is enhanced according to the local intensity characteristics. Then, potential target regions are proposed by corner detection to ensure high detection rate of the method. Finally, the potential target regions are fed into the classifier based on convolutional neural network to eliminate the non-target regions, which can effectively suppress the complex background clutter. Extensive experiments demonstrate that the proposed method can effectively reduce the false alarm rate, and outperform other state-of-the-art methods in terms of subjective visual impression and quantitative evaluation metrics.

Infrared Small Target Detection via Nonconvex Tensor Fibered Rank Approximation

2021 ◽  
pp. 1-21
Author(s):  
Xuan Kong ◽  
Chunping Yang ◽  
Siying Cao ◽  
Chaohai Li ◽  
Zhenming Peng
Keyword(s):  
Target Detection ◽  
Small Target ◽  
Small Target Detection ◽  
Rank Approximation ◽  
Infrared Small Target
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