Abstract
A novel approach for image demosaicking based on adaptive lattice-aware filter (ALF) and global refinement unit (GRU) is proposed in this work. We generate ALFs dynamically, which are adaptive to positions of pixels within color lattices in a color filter array, to obtain a locally demosaicked image. We then refine the locally demosaicked image using GRU to exploit global information, as well as local information. To extend the receptive fields efficiently, we adopt dilated convolutions in GRU. Experimental results demonstrate that the proposed algorithm provides the state-of-the-art performances in standard demosaicking datasets.
Original language | English |
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Title of host publication | 2020 IEEE International Conference on Image Processing, ICIP 2020 - Proceedings |
Publisher | IEEE Computer Society |
Pages | 483-487 |
Number of pages | 5 |
ISBN (Electronic) | 9781728163956 |
DOIs | |
State | Published - Oct 2020 |
Event | 2020 IEEE International Conference on Image Processing, ICIP 2020 - Virtual, Abu Dhabi, United Arab Emirates Duration: 25 Sep 2020 → 28 Sep 2020 |
Publication series
Name | Proceedings - International Conference on Image Processing, ICIP |
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Volume | 2020-October |
ISSN (Print) | 1522-4880 |
Conference
Conference | 2020 IEEE International Conference on Image Processing, ICIP 2020 |
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Country/Territory | United Arab Emirates |
City | Virtual, Abu Dhabi |
Period | 25/09/20 → 28/09/20 |
Bibliographical note
Publisher Copyright:© 2020 IEEE.
Keywords
- adaptive filters
- Bayer pattern
- convolutional neural networks
- Demosaicking