计算机工程与应用 ›› 2007, Vol. 43 ›› Issue (27): 100-104.

• 学术探讨 • 上一篇    下一篇

基于Bivariate模型的非抽取小波域图像复原

程 村   

  1. 北京工商大学 数理系 高等数学教研室,北京 100037
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2007-09-21 发布日期:2007-09-21
  • 通讯作者: 程 村

Bivariate model based image restoration in un-decimated wavelet domain

CHENG Cun   

  1. Department of Mathematics and Physics,Beijing Technology and Business University,Beijing 100037,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-09-21 Published:2007-09-21
  • Contact: CHENG Cun

摘要: 将Bivariate模型引入到图像复原中,以Bivariate概率分布函数作为自然图像小波系数向量的先验模型。从图像复原的Bayesian理论出发,提出基于Bivariate概率分布函数非抽取小波域的图像复原算法,并从自适应规整化的角度来分析该算法的有效性。通过对4幅标准测试图像复原实验,并将该算法复原结果与其他3种人们熟知的图像复原算法效果进行对比来证明该算法的有效性。

关键词: Bivariate概率分布函数, 图像复原, 非抽取小波变换, 共轭梯度法

Abstract: Regards the Bivairate Probability Distribution Function(PDF) as the apriori distribution of wavelet transform coefficients of natural images,and proposes an image restoration algorithm based on Bivariate distributions of un-decimated wavelet domain from the view of Bayesian theory.Discusses this restoration algorithm from the view of local adaptive regularization.At last,verifies this algorithm through performing experiments with four standard testing images and comparing with other some well-known restoration algorithms.

Key words: Biavariate Probability Distribution Function, image restoration, un-decimated wavelet transform, conjugate gradient method