典型文献
Infrared image enhancement based on adaptive weighted guided filter
文献摘要：
The physical principle of infrared imaging leads to the low contrast of the whole image,the blurring of contour and edge details,and it is also sensitive to noise.To improve the quality of infrared image and visual effect,an adaptive weighted guided filter(AWGF)for infrared image enhancement algorithm was proposed.The core idea of AWGF algorithm is to propose an adaptive strategy to update the weights of guided filter(GF)parameters,which not only improves the accuracy of regularization parameter estimation in GF theory,but also achieves the purpose of removing infrared image noise and improving its detail contrast.A large number of real infrared images were used to verify AWGF algorithm,and good experimental results were obtained.Compared with other guided filtering algorithms,the halo phenomenon at the edge of infrared images processed by the AWGF algorithm is significantly avoided,and the evaluation parameter values of information entropy(IE),average gradient(AG),and moment of inertia(MI)are relatively high.This shows that the quality of infrared image processed by the AWGF algorithm is better.
文献关键词：
中图分类号：
作者姓名：
Lu Ying;Huang Shiqi;Wang Wenqing;Sun Ke
作者机构：
School of Automation,Xi'an University of Posts and Telecommunications,Xi'an 710121,China;Xi'an Key Laboratory of Advanced Control and Intelligent Processing,Xi'an University of Posts and Telecommunications,Xi'an 710121,China
文献出处：
引用格式：
[1]Lu Ying;Huang Shiqi;Wang Wenqing;Sun Ke-.Infrared image enhancement based on adaptive weighted guided filter)[J].中国邮电高校学报（英文版）,2022(02):73-84
A类：
AWGF
B类：
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AB值：
0.513436
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