基于Moreau包络与迭代重加权策略的图像深度恢复
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TP391.41

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中国民用航空局飞行技术与飞行安全科研基地基金项目(FZ2020ZZ02)


Image Depth Restoration Based on Moreau Envelope and Iterative Reweighting Strategy
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    摘要:

    为了解决现有的深度恢复方法存在的局限性,提出了一种基于Moreau包络与迭代重加权策略的图像深度恢复方法。提出了一种基于Moreau包络的非凸惩罚函数,提高了模型的先验稀疏性,同时保持了模型的凸性,并对算法的收敛性进行了分析。然后引入了一种迭代重加权算法处理颜色不一致问题。此外,还提出了一种加速算法将深度观测矩阵转换到傅里叶域进行快速处理时的非均匀下采样问题。最后数据集实验结果表明,该方法能够处理各种类型的深度退化,在恢复精度和运行时间方面都取得了良好的效果。

    Abstract:

    In order to solve the limitations of existing depth restoration methods, an image depth restoration method based on Moreau envelope and iterative re-weighting strategy is proposed. A non convex penalty function based on Moreau envelope is proposed, which improves the prior sparsity of the model and keeps the convexity of the model. The convergence of the algorithm is analyzed. Then an iterative re-weighting algorithm is introduced to deal with the depth color inconsistency problem. In addition, an accelerated algorithm is proposed to transform the depth observation matrix into Fourier domain for fast processing. Finally, the experimental results of data sets show that the method can deal with various types of deep degradation, and has achieved good results in terms of recovery accuracy and running time.

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路晶. 基于Moreau包络与迭代重加权策略的图像深度恢复[J]. 科学技术与工程, 2021, 21(33): 14227-14237.
Lu Jing. Image Depth Restoration Based on Moreau Envelope and Iterative Reweighting Strategy[J]. Science Technology and Engineering,2021,21(33):14227-14237.

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  • 收稿日期:2021-03-27
  • 最后修改日期:2021-09-27
  • 录用日期:2021-08-23
  • 在线发布日期: 2021-11-23
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