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《Infrared Technology》 2014-03
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Infrared Image Denoising Based on Particle Filter Resample Algorithm

LI Dan;WANG Hong-tao;Henan University of Animal Husbandry and Economy;  
According to the characteristics of infrared image denoising,resample filter algorithm is presented.Firstly,the probability density function of Chapman-Kolmogorov equation is used to predict the state of the particle swarm system space,then small particle is removed in accordance with resample weights,those particles with larger weight is retained,and are sampled many times;then the effective particle number threshold is set to prevent particle degradation in particle weight,which is divided into large,medium,and small ones.Medium weight particle being kept,big and small weight particles are combined to generate new particles.Through the Thompson-Taylor algorithm new particles are randomly selected to be resampled.Finally denoising model using two kinds of noise hybrid Bimodal Noise Model and the algorithm flow is given.The simulation results show that the algorithm proposed in this paper not only denoise image effectively but also retain important information at the same time.
【CateGory Index】: TP391.41
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