Blind moving image restoration based on sparse representation and Weber's law

LIU Cheng-yun; CHANG Fa-liang

doi:10.3788/OPE.20152302.0600

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Blind moving image restoration based on sparse representation and Weber's law

更新时间：2020-08-13

- Blind moving image restoration based on sparse representation and Weber's law
- Optics and Precision Engineering Vol. 23, Issue 2, Pages: 600-608(2015)
- 作者机构：
  
  山东大学控制科学与工程学院,山东济南,250061
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20152302.0600
  CLC： TP391.4
- Received：25 September 2014，
  
  Revised：04 November 2014，
  
  Published：25 February 2015
- 稿件说明：
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刘成云, 常发亮,. 基于稀疏表示和Weber定律的运动图像盲复原[J]. 光学精密工程, 2015,23(2): 600-608

LIU Cheng-yun, CHANG Fa-liang,. Blind moving image restoration based on sparse representation and Weber's law[J]. Editorial Office of Optics and Precision Engineering, 2015,23(2): 600-608
刘成云, 常发亮,. 基于稀疏表示和Weber定律的运动图像盲复原[J]. 光学精密工程, 2015,23(2): 600-608 DOI： 10.3788/OPE.20152302.0600.

LIU Cheng-yun, CHANG Fa-liang,. Blind moving image restoration based on sparse representation and Weber's law[J]. Editorial Office of Optics and Precision Engineering, 2015,23(2): 600-608 DOI： 10.3788/OPE.20152302.0600.

摘要

针对运动过程中视觉图像易产生运动模糊的问题

提出了一种基于稀疏表示和Weber定律相结合的图像盲复原方法。该方法利用冲击滤波器预测模糊图像的显著边缘梯度

并用多尺度策略由粗到细进行模糊核的估计。然后

对图像盲复原模型进行稀疏正则化约束

并结合反映人类视觉特性的Weber定律对合成模糊图像和真实模糊图像进行盲复原。实验结果表明

本文采用的盲复原算法的性能指标和图像的纹理都达到了较优的复原效果。与近年较好的Rob Fergus去模糊方法和Xu Li去模糊方法相比

对Lena模糊图去模糊后的结构相似度(SSIM)为0.762 4

峰值信噪比(PSNR)提高了1.82~2.99 dB;对Cameraman模糊图去模糊后的结构相似度(SSIM)为0.8589

PSNR提高了2.46~5.58 dB。另外

本文方法降低了复原图像的边界伪影

符合人的视觉感知特性。

Abstract

For the motion blur problem of a visual image produced in moving processing

a blind image restoration method based on sparse representation and Weber's law is proposed. The method uses a shock filter to predict the sharp edges of blurred images

and a multi-scale strategy to estimate the blur kernel from a coarse estimation to a fine one. The sparse representation is treated as a priori knowledge for regularization constraint of blind image restoration model

and the Weber's law which reflects the human visual characteristics is combined to conduct blind restoration for the synthetic blurred image and the real blurred image. Experimental results show that the proposed method achieves better restoration results both for the performance indexes and the image textures. As compared with the Rob Fergus's method and Xu Li's method developed in recent years

it shows that the structural similarity (SSIM) is 0.762 4 and the Peak Signal to Noise Ratio (PSNR) is improved by 1.82 dB to 2.99 dB for the deblurred Lena image

and the SSIM is 0.858 9; and the PSNR has improved by 2.46 dB to 5.58 dB for the deblurred Cameraman image. Moreover

the proposed method reduces the boundary artifacts of the restored image

which is better consistent with human visual perception characteristics.

关键词

Keywords

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