A new approach for infrared image contrast enhancement

2006 ◽  
Author(s):  
Mingli Shao ◽  
Guixi Liu ◽  
Xianhong Liu ◽  
Dongbo Zhu
Keyword(s):  
Contrast Enhancement ◽  
Infrared Image ◽  
Image Contrast ◽  
New Approach ◽  
Image Contrast Enhancement

Infrared Image Contrast Enhancement Based on Haze Remove Method

2015 ◽  
Vol 42 (1) ◽  
pp. 0113004
Author(s):  
李毅 Li Yi ◽  
张云峰 Zhang Yunfeng ◽  
张强 Zhang Qiang ◽  
耿爱辉 Geng Aihui ◽  
陈娟 Chen Juan
Keyword(s):  
Contrast Enhancement ◽  
Infrared Image ◽  
Image Contrast ◽  
Image Contrast Enhancement

Infrared Image Contrast Enhancement Based on Modified Particle Swarm Optimization

2013 ◽  
Vol 760-762 ◽  
pp. 1389-1393
Author(s):  
Ren Tao Zhao ◽  
You Yu Wang ◽  
Hua De Li ◽  
Jun Tie
Keyword(s):  
Particle Swarm Optimization ◽  
Contrast Enhancement ◽  
Particle Swarm ◽  
Infrared Image ◽  
Optimal Solution ◽  
Image Contrast ◽  
Swarm Optimization ◽  
Modified Particle Swarm Optimization ◽  
Image Contrast Enhancement ◽  
Modified Pso

Adaptive infrared image contrast enhancement is presented based on modified particle swarm optimization (PSO) and incomplete Beta Function. On the basis of traditional PSO, modified PSO integrates into the theory of Multi-Particle Swarm and evolution theory algorithm. By using separate search space optimal solution of multiple particles, the global search ability is improved. And in the iteration procedures, timely adjustment of acceleration coefficients is convenient for PSO to find the global optimal solution in the later iteration. Through infrared image simulation, experimental results show that the modified PSO is better than the standard PSO in computing speed and convergence.

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