计算机应用 ›› 2011, Vol. 31 ›› Issue (08): 2201-2203.DOI: 10.3724/SP.J.1087.2011.02201

• 图形图像技术 • 上一篇    下一篇

图像恢复的正则化Gmres方法

闵涛,赵苗苗,成瑶   

  1. 西安理工大学 理学院,西安710054
  • 收稿日期:2011-03-07 修回日期:2011-04-22 发布日期:2011-08-01 出版日期:2011-08-01
  • 通讯作者: 赵苗苗
  • 作者简介:闵涛(1963-),男,陕西西安人,教授,博士,主要研究方向:科学工程计算、计算机模拟、图像处理;赵苗苗(1986-),女,陕西咸阳人,硕士研究生,主要研究方向:科学工程计算、计算机模拟;成瑶(1985-),女,山西霍州人,硕士研究生,主要研究方向:科学工程计算、计算机模拟。
  • 基金资助:

    国家自然科学基金资助项目(50979088)

Regularized Gmres method of image restoration

Tao MIN,Miao-miao ZHAO,Yao CHENG   

  1. School of Sciences, Xi'an University of Technology, Xi'an Shaanxi 710054, China
  • Received:2011-03-07 Revised:2011-04-22 Online:2011-08-01 Published:2011-08-01
  • Contact: Miao-miao ZHAO

摘要: 在处理具有线性的、空间位移不变的成像系统所成的图像恢复问题时,提出了一种基于Krylov向量完全正交化的正则化Gmres方法。该算法考虑了图像恢复中的不适定性及计算时的复杂性两个方面,将正则化算法与广义极小残余算法相结合,通过正则化方法将模型离散后的积分方程转化为一适定问题,然后利用广义极小残余算法得到结果。在数值模拟时,对不同的方法进行了对比分析,结果表明所选的方法能够明显改善图像恢复的质量。

关键词: 成像系统, 退化模型, 图像恢复, 不适定性, 正则化Gmres法

Abstract: Dealing with the restoration problem of image through the linear, spatial displacement of the imaging system, a completely orthogonal regularization Gmres method based on Krylov vectors was proposed. The proposed algorithm considered the ill-posedness in image restoration and the complexity of the calculation, and combined the regularization algorithm with the generalized minimal residual algorithm. By introducing the regularization method, the discredited integral equation was transformed into a posed problem of discrete and the numerical solution was obtained by generalized minimal residual algorithm. In the numerical simulation, the different methods were compared. The experimental results show that the proposed method can significantly improve the quality of image restoration.

Key words: imaging system, degradation model, image restoration, ill-posedness, regularized Gmres method

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