JOURNAL ARTICLE

Single Infrared Image Optical Noise Removal Using a Deep Convolutional Neural Network

Xiaodong KuangXiubao SuiYuan LiuQian ChenGuohua Gu

Year: 2017 Journal:   IEEE photonics journal Vol: 10 (2)Pages: 1-15   Publisher: Institute of Electrical and Electronics Engineers

Abstract

In this paper, we propose a deep learning method for single infrared image optical noise removal. With a fully convolutional neural network, it is able to eliminate the optical noise in single infrared image. Our architecture consists of two networks: a denoising network and a conditional discriminator. The denoising network takes a noise image as input and outputs a denoising result, while the discriminator tries to make the output look more like the target. Actually, only in the testing phase, this method is feed-forward. Significant image quality in experiments is achieved compared with the existing method.

Keywords:
Discriminator Computer science Artificial intelligence Noise reduction Convolutional neural network Noise (video) Pattern recognition (psychology) Image quality Computer vision Image (mathematics) Image denoising Telecommunications

Metrics

103
Cited By
6.16
FWCI (Field Weighted Citation Impact)
45
Refs
0.98
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Spectroscopy Techniques in Biomedical and Chemical Research
Life Sciences →  Biochemistry, Genetics and Molecular Biology →  Biophysics
Advanced Image Fusion Techniques
Physical Sciences →  Engineering →  Media Technology
Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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