Deep Learning for Image Denoising: A Survey

Author:

Tian Chunwei,Xu Yong,Fei Lunke,Yan Ke

Publisher

Springer Singapore

Reference50 articles.

1. Ahn, B., Cho, N.I.: Block-matching convolutional neural network for image denoising (2017). arXiv:1704.00524

2. Arora, S., Bhaskara, A., Ge, R., Ma, T.: Provable bounds for learning some deep representations. In: International Conference on Machine Learning, pp. 584–592 (2014)

3. Bako, S., Vogels, T., McWilliams, B., Meyer, M., Novák, J., Harvill, A., Sen, P., Derose, T., Rousselle, F.: Kernel-predicting convolutional networks for denoising monte carlo renderings. ACM Trans. Graph 36(4), 97 (2017)

4. Bengio, Y., Simard, P., Frasconi, P.: Learning long-term dependencies with gradient descent is difficult. IEEE Trans. Neural Netw. 5(2), 157–166 (1994)

5. Buades, A., Coll, B., Morel, J.-M.: A non-local algorithm for image denoising. In: CVPR 2005. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2005, vol. 2, pp. 60–65. IEEE (2005)

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