TY - GEN
T1 - Adaptive Lattice-Aware Image Demosaicking Using Global and Local Information
AU - Kim, Ji Soo
AU - Ko, Keunsoo
AU - Kim, Chang Su
N1 - Funding Information:
This work was supported in part by the MSIT, Korea, under the ITRC support program (IITP-2020-2016-0-00464) supervised by the IITP and in part by the National Research Foundation of Korea (NRF) through the Korea Government (MSIP) under Grant NRF-2018R1A2B3003896.
Publisher Copyright:
© 2020 IEEE.
PY - 2020/10
Y1 - 2020/10
N2 - 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.
AB - 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.
KW - Bayer pattern
KW - Demosaicking
KW - adaptive filters
KW - convolutional neural networks
UR - http://www.scopus.com/inward/record.url?scp=85098617306&partnerID=8YFLogxK
U2 - 10.1109/ICIP40778.2020.9190936
DO - 10.1109/ICIP40778.2020.9190936
M3 - Conference contribution
AN - SCOPUS:85098617306
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 483
EP - 487
BT - 2020 IEEE International Conference on Image Processing, ICIP 2020 - Proceedings
PB - IEEE Computer Society
T2 - 2020 IEEE International Conference on Image Processing, ICIP 2020
Y2 - 25 September 2020 through 28 September 2020
ER -