J Shanghai Jiaotong Univ Sci ›› 2023, Vol. 28 ›› Issue (6): 793-801.doi: 10.1007/s12204-022-2453-2
侯舒娟,朱文萍,李海
接受日期:
2021-03-29
出版日期:
2023-11-28
发布日期:
2023-12-04
HOU Shujuan* (侯舒娟),ZHU Wenping (朱文萍),LI Hai (李海)
Accepted:
2021-03-29
Online:
2023-11-28
Published:
2023-12-04
摘要: 图像复原是将退化图像恢复至接近理想图像的过程。以前的研究大多集中在单一失真图像上,然而大多数真实图像都经历了多种失真,单一失真图像复原算法无法有效提高图像质量。此外,现有的几种混合失真图像复原算法不具备处理单一失真的兼容性。因此,本文提出了一种基于分阶段训练的端到端神经网络。具体来说,该网络选择了三个典型的图像复原任务:图像去噪、图像修复和图像超分辨率。整个训练过程分为单一失真训练、两种类型的混合失真训练和三种类型的混合失真训练。损失函数的设计是基于深度监督的思想。实验结果表明,该方法不仅在混合失真图像复原方面优于其他方法,而且适用于单一失真图像复原。
中图分类号:
侯舒娟,朱文萍,李海. 混合失真图像恢复的分阶段训练[J]. J Shanghai Jiaotong Univ Sci, 2023, 28(6): 793-801.
HOU Shujuan* (侯舒娟),ZHU Wenping (朱文萍),LI Hai (李海). Stagewise Training for Hybrid-Distorted Image Restoration[J]. J Shanghai Jiaotong Univ Sci, 2023, 28(6): 793-801.
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