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计算机工程 ›› 2010, Vol. 36 ›› Issue (19): 213-215,218. doi: 10.3969/j.issn.1000-3428.2010.19.075

• 图形图像处理 • 上一篇    下一篇

一种改进的受限制自适应图像复原算法

来彦栋,陈 奋,刘晓云   

  1. (电子科技大学自动化工程学院,成都 611731)
  • 出版日期:2010-10-05 发布日期:2010-09-27
  • 作者简介:来彦栋(1984-),男,硕士研究生,主研方向:图像复原,控制理论与控制工程;陈 奋、刘晓云,副教授
  • 基金资助:
    国家自然科学基金-青年科学基金资助项目(40801171)

Improved Constrained Self-adaptive Image Restoration Algorithm

LAI Yan-dong, CHEN Fen, LIU Xiao-yun   

  1. (School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China)
  • Online:2010-10-05 Published:2010-09-27

摘要: 利用Wiener滤波或约束最小二乘方法复原的图像在图像灰度值发生跳变处会出现振铃式的波纹。受限制自适应图像复原算法对复原和平滑加以局部的适应性控制,有效地克服振铃波纹。在受限制自适应图像复原算法的基础上,通过提高加权数组的精细程度,改善复原的自适应控制能力,采用Neumann边界条件消除边界截断引起的寄生波纹。实验结果表明改进算法的复原效果较优。

关键词: 自适应图像复原, Sobel算子, Neumann边界条件

Abstract: The restored image which takes advantage of Wiener filter or least squares algorithm occur ringing waves in the place where the gray scale value of image is jumping. The constrained self-adaptive image restoration algorithm effectively overcomes the ringing waves through local adaptive control of restoration and smoothness. On the basis of the constrained self-adaptive image restoration algorithm, the ability of self-adaptive control of restoration is improved by increasing the precision of the weighted array, and the artifacts occurred by boundary truncation are removed by adopting Neumann boundary condition. Experimental results show that the improved algorithm gains better recovery effect.

Key words: self-adaptive image restoration, Sobel operator, Neumann boundary condition

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