计算机科学
人工智能
降噪
旋光法
模式识别(心理学)
计算机视觉
极化(电化学)
图像处理
图像(数学)
光学
物理
散射
物理化学
化学
作者
Hedong Liu,Xiaobo Li,Zhenzhou Cheng,Kun Liu,Jingsheng Zhai,Haofeng Hu
出处
期刊:Optics Letters
[The Optical Society]
日期:2023-09-08
卷期号:48 (18): 4821-4821
被引量:2
摘要
In this Letter, we present a self-supervised method, polarization to polarization (Pol2Pol), for polarimetric image denoising with only one-shot noisy images. First, a polarization generator is proposed to generate training image pairs, which are synthesized from one-shot noisy images by exploiting polarization relationships. Second, the Pol2Pol method is extensible and compatible, and any network that performs well in supervised image denoising tasks can be deployed to Pol2Pol after proper modifications. Experimental results show Pol2Pol outperforms other self-supervised methods and achieves comparable performance to supervised methods.
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