Small Target Detection Algorithm Based on Average Absolute Difference Maximum and Background Forecast

2007 ◽  
Vol 28 (1) ◽  
pp. 87-97 ◽  
Author(s):  
Zhenxue Chen ◽  
Guoyou Wang ◽  
Jianguo Liu ◽  
Chengyun Liu
Author(s):  
ZHEN-XUE CHEN ◽  
CHENG-YUN LIU ◽  
FA-LIANG CHANG

It is an important and challenging problem to detect small targets in clutter scene and low SNR (Signal Noise Ratio) in infrared (IR) images. In order to solve this problem, a method based on feature salience is proposed for automatic detection of targets in complex background. Firstly, in this paper, the method utilizes the average absolute difference maximum (AADM) as the dissimilarity measurement between targets and background region to enhance targets. Secondly, minimum probability of error was used to build the model of feature salience. Finally, by computing the realistic degree of features, this method solves the problem of multi-feather fusion. Experimental results show that the algorithm proposed shows better performance with respect to the probability of detection. It is an effective and valuable small target detection algorithm under a complex background.


2015 ◽  
Author(s):  
Ying Zhao ◽  
Gang Liu ◽  
Huixin Zhou ◽  
Hanlin Qin ◽  
Xiao Li ◽  
...  

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