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NTIRE 2019 Challenge on Real Image Denoising: Methods and Results

Abdelrahman Abdelhamed,Radu Timofte,Michael S. Brown,Songhyun Yu,Bumjun Park,Jechang Jeong,Seung-Won Jung,Dong-Wook Kim,Jae-Ryun Chung,Jiaming Liu,Yuzhi Wang,Chi-Hao Wu,Qin Xu,Chuan Wang,Shaofan Cai,Yifan Ding,Haoqiang Fan,Jue Wang,Kai Zhang,Wangmeng Zuo,Magauiya Zhussip,Dong Won Park,Shakarim Soltanayev,Se Young Chun,Zhiwei Xiong,Chang Chen,Muhammad Haris,Kazutoshi Akita,Tomoki Yoshida,Greg Shakhnarovich,Norimichi Ukita,Syed Waqas Zamir,Aditya Arora,Salman Khan,Fahad Shahbaz Khan,Ling Shao,Sung-Jea Ko,Dong-Pan Lim,Seung-Wook Kim,Seo-Won Ji,Sang-Won Lee,Wenyi Tang,Yuchen Fan,Yuqian Zhou,Ding Liu,Thomas S. Huang,Deyu Meng,Lei Zhang,Hongwei Yong,Yiyun Zhao,Pengliang Tang,Yue Lu,Raimondo Schettini,Simone Bianco,Simone Zini,Chi Li,Yang Wang,Zhiguo Cao

IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops（2019）

Cited 99|Views197
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Abstract
This paper reviews the NTIRE 2019 challenge on real image denoising with focus on the proposed methods and their results. The challenge has two tracks for quantitatively evaluating image denoising performance in (1) the Bayer-pattern raw-RGB and (2) the standard RGB (sRGB) color spaces. The tracks had 216 and 220 registered participants, respectively. A total of 15 teams, proposing 17 methods, competed in the final phase of the challenge. The proposed methods by the 15 teams represent the current state-of-the-art performance in image denoising targeting real noisy images.
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Key words
NTIRE 2019 challenge,Bayer-pattern raw-RGB,standard RGB color spaces,noisy images,quantitative image denoising performance evaluation
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