Learning Camera-Aware Noise Models

Ke Chi Chang, Ren Wang, Hung Jin Lin, Yu Lun Liu, Chia Ping Chen, Yu Lin Chang, Hwann Tzong Chen*

*此作品的通信作者

研究成果: Conference contribution同行評審

15 引文 斯高帕斯(Scopus)

摘要

Modeling imaging sensor noise is a fundamental problem for image processing and computer vision applications. While most previous works adopt statistical noise models, real-world noise is far more complicated and beyond what these models can describe. To tackle this issue, we propose a data-driven approach, where a generative noise model is learned from real-world noise. The proposed noise model is camera-aware, that is, different noise characteristics of different camera sensors can be learned simultaneously, and a single learned noise model can generate different noise for different camera sensors. Experimental results show that our method quantitatively and qualitatively outperforms existing statistical noise models and learning-based methods. The source code and more results are available at https://arcchang1236.github.io/CA-NoiseGAN/.

原文English
主出版物標題Computer Vision – ECCV 2020 - 16th European Conference, 2020, Proceedings
編輯Andrea Vedaldi, Horst Bischof, Thomas Brox, Jan-Michael Frahm
發行者Springer Science and Business Media Deutschland GmbH
頁面343-358
頁數16
ISBN(列印)9783030585853
DOIs
出版狀態Published - 2020
事件16th European Conference on Computer Vision, ECCV 2020 - Glasgow, United Kingdom
持續時間: 23 8月 202028 8月 2020

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
12369 LNCS
ISSN(列印)0302-9743
ISSN(電子)1611-3349

Conference

Conference16th European Conference on Computer Vision, ECCV 2020
國家/地區United Kingdom
城市Glasgow
期間23/08/2028/08/20

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