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초록·키워드 목차

Various methods, including block-matching and 3D filtering (BM3D), have been proposed for image denoising. Recently, studies on deep learning methods for image denoising have been on the rise. In this paper, we propose a new structure for a deep neural network that improves image denoising performance. Among the existing deep neural networks, we improve U-net, which is widely used for image restoration, through the inclusion of pre-processing and post-processing and by modifying each of its stages. Extensive simulations show that the proposed structure performs very well for a wide range of noise levels with a single trained parameter, and it exhibits superior image denoising performance compared to conventional deep neural networks. #Image denoising #Deep learning #U-net #New structure #Improved U-net

Abstract
1. Introduction
2. Image Denoising Method
3. Improving U-net for Image Denoising
4. Performance Evaluation
5. Conclusion
References

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