基于奇异值分解的运动模糊图像广义逆恢复方法

鲁晓东

鲁晓东. 基于奇异值分解的运动模糊图像广义逆恢复方法[J]. 应用光学, 2013, 34(1): 90-94.
引用本文: 鲁晓东. 基于奇异值分解的运动模糊图像广义逆恢复方法[J]. 应用光学, 2013, 34(1): 90-94.
shu
LU Xiao-dong. Restoration of motion-blurred image by generalizedinverse method based on SVD[J]. Journal of Applied Optics, 2013, 34(1): 90-94.
Citation: LU Xiao-dong. Restoration of motion-blurred image by generalizedinverse method based on SVD[J]. Journal of Applied Optics, 2013, 34(1): 90-94.
shu

基于奇异值分解的运动模糊图像广义逆恢复方法

  • 浙江海洋学院 物理实验中心,浙江 舟山 316000

详细信息
    通讯作者:

    鲁晓东（1971-），男，浙江舟山人，硕士，主要从事图像与信号处理方面的研究工作。 Email: lxd7725@163.com

  • 中图分类号: TP391.41

Restoration of motion-blurred image by generalizedinverse method based on SVD

  • Physical Experiment Centre,Zhejiang Ocean University,Zhoushan 316000,China

摘要

    摘要
  • 摘要: 当线性模型应用于运动模糊模糊图像的恢复时，方程的最小二乘解是恢复图像的最优线性无偏估计。由于图像退化过程的不适定性，当观测值受到噪声干扰时，该解往往会远偏离真值。为了克服这个问题，通过对退化矩阵的奇异值分解，提取其不易受干扰的子空间，用该空间重构的逆矩阵具有良好抑噪能力，使图像在较长的运动模糊尺度内恢复时保持较低的失真。
    Abstract: When a method based on linear model is applied for motion-blurred image restoration, its least square solution is the best linear unbiased estimator for the restoration. Because of the ill-conditioned degeneration of the image, this solution always diverges far from the original value in the case of noise jamming. In order to overcome the shortage, some subspaces not susceptible to noise were extracted by singular value decomposition (SVD) of degenerate matrix. A more robust inverse matrix was reconstructed on these spaces and it ensured the restored image had less distortion in a longer blurred length.
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  • 刊出日期:  2013-01-14

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