北京航空航天大学学报

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消除相机异常值的饱和模糊图像盲复原

仇翔   

  1. 中国科学院长春光学精密机械与物理研究所
  • 收稿日期:2017-04-05 修回日期:2017-05-09 发布日期:2017-06-27
  • 通讯作者: 仇翔
  • 基金资助:
    高空间分辨率电子倍增超光谱成像信噪比评价与测试方法研究

Saturated blurred image blind restoration with removing camera outliers

  • Received:2017-04-05 Revised:2017-05-09 Published:2017-06-27

摘要: 由于相机异常值严重影响模糊核的正确估计,使传统图像复原算法效果不佳、细节丢失严重、人工痕迹明显,为此本文提出了一种基于消除相机异常值的饱和模糊图像盲复原算法。首先,根据饱和图像灰度特性建立L1正则化模型,添加超拉普拉斯先验提取图像显著边缘。接着,针对S型函数无法完全滤除边缘中的饱和像素,我们提出一种模糊核镜像辅助函数,通过设定阈值可以有效消除异常值。最后,分析异常值对模糊核估计的影响,建立基于异常值感知的盲反卷积模型,针对迭代求解中二次型问题,采用迭代加权最小二乘法运算得到恢复图像。通过对多幅不同类型的饱和模糊图像进行实验,结果显示复原图像平均灰度梯度高达12.689,图像信息熵达到7.681,处理255*255图像只需6.08s,可以将相机异常值的影响降到最低,正确估计模糊核函数,保留清晰细节信息的同时显著提高了运算速度,优于当今最先进的图像盲复原算法。

关键词: 图像盲复原, 相机异常值, 饱和图像, 超拉普拉斯先验, S型函数, 迭代加权最小二乘法

Abstract: Camera outliers seriously affect estimating the blur kernel, so the traditional image restoration algorithm is ineffective, serious loss of details, artifacts, this paper proposed a saturated blurred image blind restoration algorithm with removing camera outliers. First, the L1 regularization model is established according to the gray characteristics of the saturated image, and a hyper-Laplace prior is used to extract the salient edges of the image. Then aiming at the S function can not completely filter the saturated pixels in the edge, we propose a blur kernel auxiliary function which can effectively eliminate outliers by setting threshold. Finally, by analyzing the influence of outliers of blur kernel estimating ,we establish blind deconvolution model based on outlier-aware. Aiming at quadratic problem, the iterative weighted least squares method is used to obtain the restored image. Through experiments on several different saturated blurred images,the results show that average gray level gradient up to 12.689, image entropy up to 7.681,processing 255*255 images requires only 6.08s. It can effectively reduce the influence of camera outliers of estimating kernel, retain the integrity of clear details and significantly improve the speed of operation. Which is better than the most advanced image blind restoration algorithm.

Key words: Blind image restoration, Camera outliers, Saturated image, Hyper-Laplace prior, sigmoid function, the iterated weighted least squares


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