计算机科学 ›› 2010, Vol. 37 ›› Issue (7): 270-272.

• 图形图像 • 上一篇    下一篇

一种有效保持边缘特征的散焦模糊图像复原方法

肖泉,丁兴号,廖英豪   

  1. (厦门大学信息科学与技术学院 厦门361005),(厦门大学水声通信与海洋信息技术教育部重点实验室 厦门361005)
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受福建省自然科学基金(2008J0032,2009J01301,2009J01302),厦门大学985二期信息创新平台资助项目(0000-X07204),厦门市科技计划高校创新项目(3502220083006)资助。

Novel Edge-preserving Algorithm for Defocus Blurred Image Restoration 降

XIAO Quan,DING Xing-hao,LIAO Ying-hao   

  • Online:2018-12-01 Published:2018-12-01

摘要: 图像复原过程中图像的主观视觉质量与图像的局部细节信息之间密切相关。针对散焦模糊图像,提出一种新的图像复原方法。所提方法在传统双边总变分正则化方法基础上,通过引入一种具有结构自适应的局部权值函数,构造了一种新的图像复原目标函数。该目标函数综合考虑了图像的全局与局部统计特性,即在整体保真情况下还充分考虑了图像的局部结构信息,使得所提复原方法能更有效地保持图像的边缘等细节信息。与传统13"I'V正则化方法的比较实验表明,所提方法在边缘保持方面更有效,复原后的图像具有更好的主、客观视觉质量。

关键词: 图像复原,点扩散函数,双边总变分,局部权值函数

Abstract: Relevant research on image restoration indicates that image's subjective visual quality is closely related to its local details. A novel restoration algorithm for defocus blurred image was proposed. The proposed algorithm based on BTV regularization framework by introducing a local adaptive weighted function constructs a new cost function for imargc restoration. hhis cost function which not only takes into account the global data-fidelity, but also considers the local statistical properties of image,meaning to fully consider the local structural features of image under global data-fidelity,hence behaves much better in edge preservation. Experimental results confirm the effectiveness of the proposed method.The image is restored with better subjective and objective visual quality, compared with other methods such as traditional B丁V regularization approach.

Key words: Image restoration, Point spread function, Bilateral total variation, Local weighted function

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