Single Infrared Image Stripe Noise Removal Using Deep Convolutional Networks

被引:82
作者
Kuang, Xiaodong [1 ]
Sui, Xiubao [1 ]
Chen, Qian [1 ]
Gu, Guohua [1 ]
机构
[1] Nanjing Univ Sci & Technol, Nanjing 210094, Jiangsu, Peoples R China
来源
IEEE PHOTONICS JOURNAL | 2017年 / 9卷 / 04期
关键词
Stripe noise removal; infrared image; deep convolutional neural networks; NONUNIFORMITY CORRECTION; QUALITY ASSESSMENT; STATISTICS; ALGORITHM;
D O I
10.1109/JPHOT.2017.2717948
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, we present a deep learning method for single infrared image stripe noise removal. Our method is denoted as a deep convolutional neural network (CNN) that takes the noisy image as the input and outputs the clean image. The deep CNN consists of two components: 1) image denoising, substantially removing the stripe noise but losing details, 2) image denoising and super resolution, completely eliminating the residual stripe noise and restore details. Our deep CNN exhibits excellent image denoising and detail preserving performance. Meanwhile it achieves fast speed for real-time image processing. Experiments study the relationship between model parameter settings and model performance.
引用
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页数:13
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