Image denoising with local dense and adaptive global residual networks

Lulu Sun, Yongbing Zhang*, Chenggang Yan, Xiangyang Ji, Xinhong Hao, Yongdong Zhang, Qionghai Dai

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Residual Networks (ResNet) and Dense Convolutional Networks (DenseNet) have shown great success in lots of high-level computer vision applications. In this paper, we propose a novel network with Local Dense and Adaptive Global Residual (LD+AGR) frameworks for fast and accurate image denoising. More precisely, we combine local residual/dense with global residual/dense to investigate the best performance dealing with image denoising problem. In particular, local/global residual/dense means the connection way of inner/outer recursive blocks. And residual/dense represents combining layers by summation/concatenation. Furthermore, when combining skip connections, we add some adaptive and trainable scaling parameters, which could adjust automatically during training to balance the importance of different layers. Numerous experiments demonstrate that the proposed network performs favorably against the state-of-the-art methods in terms of quality and speed.

源语言英语
主期刊名Advances in Multimedia Information Processing – PCM 2018 - 19th Pacific-Rim Conference on Multimedia, 2018, Proceedings
编辑Chong-Wah Ngo, Richang Hong, Meng Wang, Wen-Huang Cheng, Toshihiko Yamasaki
出版商Springer Verlag
27-37
页数11
ISBN(印刷版)9783030007751
DOI
出版状态已出版 - 2018
活动19th Pacific-Rim Conference on Multimedia, PCM 2018 - Hefei, 中国
期限: 21 9月 201822 9月 2018

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
11164 LNCS
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议19th Pacific-Rim Conference on Multimedia, PCM 2018
国家/地区中国
Hefei
时期21/09/1822/09/18

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引用此

Sun, L., Zhang, Y., Yan, C., Ji, X., Hao, X., Zhang, Y., & Dai, Q. (2018). Image denoising with local dense and adaptive global residual networks. 在 C.-W. Ngo, R. Hong, M. Wang, W.-H. Cheng, & T. Yamasaki (编辑), Advances in Multimedia Information Processing – PCM 2018 - 19th Pacific-Rim Conference on Multimedia, 2018, Proceedings (页码 27-37). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 11164 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-00776-8_3