Detecting target with low signal to noise ratio is an fundamental technique used for automatic target recognition (ATR) in infrared imagery
and its performances make an ultimate impact on detection sensitivity and effective distance of a system.It is a leading key technique to indicate the ability of recognizing low-observable target in infrared imagery.Adaptive background estimation method is an efficient avenue to complete this task.On the basis of summarizing several current estimation means
a novel morphological filtering algorithm improved properly is proposed in this paper.Some theoretical analyses and experimental results show that this method is able to simplify operation of morphological conversion and to optimize formation of structuring elements.Consequently it can enhance the filtering result and accelerate the speed of operation as well.Moreover it is capable of preserving the property to protect signal characteristic and improving the inherent limitation not to be sensitive on fluctuation of noise and having better ability of adaptive background perception in morphological filtering algorithm.In conclusion this method is concise and efficient.It can provide good filtering results and robust adaptability to image targets with clutter background.
Cross-Modal SAR Target Detection via Progressive Knowledge Transfer
Anchor-Free Transformer Algorithm for Aerial Remote Sensing Target Detection
Application of Improved Cascade R-CNN Algorithm in Target Detection
Combination Navigation and Positioning Method for Binocular Vision Assisted PDR
Design and Optimization of Target Detection Accelerator Based on Winograd Algorithm
Related Author
ZHAO Guo-wei
JIANG Jia-qing
DONG Gang-gang
YU Jiu-yang
HU Tian-hao
DAI Yao-nan
ZHANG De-an
XIA Wen-feng
Related Institution
National Key Laboratory of Radar Signal Processing, Xidian University
Hubei Provincial Engineering Technology Research Center of Green Chemical Equipment, School of Mechanical and Electrical Engineering, Wuhan Institute of Technology
School of Science, Zhejiang Science Technology University
School of Computer and Technology (School of Artificial Intelligence), Zhejiang Science Technology University
Zhejiang Guangsha Vocational and Technical University of Construction, Dongyang