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图学学报

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一种新的图像去模糊清晰化方法

  

  1. 淮阴工学院计算机与软件工程学院,江苏淮安 223003
  • 出版日期:2018-04-30 发布日期:2018-04-30
  • 基金资助:
    国家自然科学基金项目(61403060,61603146);江苏省六大人才高峰项目(XYDXXJS-012)

A New Method for Image Deblurring and Clearness

  1. Faculty of Computer & Software Engineering, Huaiyin Institute of Technology, Huaian Jiangsu 223003, China
  • Online:2018-04-30 Published:2018-04-30

摘要: 针对在实际环境中很难得到图像去模糊所需要的大量先验知识,诸如退化模式、
点扩散函数等,提出了一种新的图像去模糊清晰化方法。首先利用高斯差分算子获得图像轮廓
信息,然后根据轮廓信息预测清晰图像过渡区,再利用清晰图像过渡区、退化图像和点扩散函
数之间的关系建立目标函数,为了克服噪声的影响,在目标函数中加入了非负性惩罚项和空间
相关性约束项,并使用滞后迭代的极小化方法来求解点扩散函数;最后通过已有的非盲目图像
复原算法复原图像。实验结果表明,该方法无需知道图像退化模式,对各种因素引起的退化图
像都能有效地复原。

关键词: 图像去模糊, 清晰化, 过渡区, 点扩散函数

Abstract: Due to the various limitations in real restoration process, it is difficult to get the image blur
mode or point spread function (PSF). A new method for image deblurring is proposed in this paper. At
first, the proposed deblurring method uses the different of Gaussian operator (DoG) to detect the
counters of blur image. Then the information of transition region of original image can be predicted
according to the contours of blur image. Then the objective function is established according to the
original image, transition region, and point spread function. In order to overcome the influence of
noise, the nonnegative penalty term and space correlation penalty term with anisotropic features are
added in objective function, and the PSF is solved using the minimization method of hysteresis
iteration. Finally, the clear image can be gained by the existing the non-blind image restoration
methods. Experimental results show that the proposed method can effectively restore the blur images
caused by various factors. It does not need to know the image blur model.

Key words: image deblurring, clearness, transition region, point spread function