北京理工大学学报
北京理工大學學報
북경리공대학학보
JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY
2010年
1期
105-108
,共4页
田卉%沈庭芝%李挺%郝兵
田卉%瀋庭芝%李挺%郝兵
전훼%침정지%리정%학병
图像恢复%粒子滤波%遗传算法%马尔可夫链蒙特卡洛(MCMC)
圖像恢複%粒子濾波%遺傳算法%馬爾可伕鏈矇特卡洛(MCMC)
도상회복%입자려파%유전산법%마이가부련몽특잡락(MCMC)
image restoration%particle filter%genetic algorithm (GA)%Markov chain Monte Carlo(MCMC)
针对粒子滤波的退化和贫化问题,提出一种GA-MCMC粒子滤波图像恢复算法. 该算法引入遗传算法(GA)全局寻优和粒子总数多样性的特性,结合马尔可夫链蒙特卡罗方法(MCMC)的收敛性,将交叉、变异和选择操作融入到粒子滤波图像恢复中,提高了粒子滤波的鲁棒性、精确性和灵活性. 实验结果表明,该算法能减少贫化和退化问题,且在对具有混合噪声的真实图像恢复效果方面显示了其优越性.
針對粒子濾波的退化和貧化問題,提齣一種GA-MCMC粒子濾波圖像恢複算法. 該算法引入遺傳算法(GA)全跼尋優和粒子總數多樣性的特性,結閤馬爾可伕鏈矇特卡囉方法(MCMC)的收斂性,將交扠、變異和選擇操作融入到粒子濾波圖像恢複中,提高瞭粒子濾波的魯棒性、精確性和靈活性. 實驗結果錶明,該算法能減少貧化和退化問題,且在對具有混閤譟聲的真實圖像恢複效果方麵顯示瞭其優越性.
침대입자려파적퇴화화빈화문제,제출일충GA-MCMC입자려파도상회복산법. 해산법인입유전산법(GA)전국심우화입자총수다양성적특성,결합마이가부련몽특잡라방법(MCMC)적수렴성,장교차、변이화선택조작융입도입자려파도상회복중,제고료입자려파적로봉성、정학성화령활성. 실험결과표명,해산법능감소빈화화퇴화문제,차재대구유혼합조성적진실도상회복효과방면현시료기우월성.
Particle filter is applied in image restoration, in order to remove degeneracy phenomenon and alleviate the sample impoverishment problem. The global optimization and particle diversity of generic algorithm(GA) are introduced, and the convergence of Markov chain Monte Carlo (MCMC) method was combined, the crossover, mutation and selection operation were used in image restoration by particle filter, to enhance the robustness, accuracy and flexibility of the particle filter. Furthermore, a new image restoration algorithm by GA-MCMC particle filter is proposed. Simulation results showed that this method can reduce the impoverishment and degeneracy problems, and from the restoration results to mixed noisy image, we can see the effectiveness and superiority of the proposed algorithm.