| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0575759 |
| utime |
20240402214439.5 |
| mtime |
20230922235959.9 |
| DOI |
10.1109/ICIP49359.2023.10221948 |
| title
(primary) (eng) |
NeRD: Neural field-based Demosaicking |
| specification |
| page_count |
5 s. |
| media_type |
E |
|
| serial |
| ARLID |
cav_un_epca*0575755 |
| ISBN |
978-1-7281-9835-4 |
| title
|
Proceedings of the 2023 IEEE International Conference on Image Processing (ICIP) |
| page_num |
1735-1739 |
| publisher |
| place |
Piscataway |
| name |
IEEE |
| year |
2023 |
|
|
| keyword |
Demosaicking |
| keyword |
neural field |
| keyword |
implicit neural representation |
| author
(primary) |
| ARLID |
cav_un_auth*0379363 |
| name1 |
Kerepecký |
| name2 |
Tomáš |
| institution |
UTIA-B |
| full_dept (cz) |
Zpracování obrazové informace |
| full_dept (eng) |
Department of Image Processing |
| department (cz) |
ZOI |
| department (eng) |
ZOI |
| full_dept |
Department of Image Processing |
| country |
CZ |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0101209 |
| name1 |
Šroubek |
| name2 |
Filip |
| institution |
UTIA-B |
| full_dept (cz) |
Zpracování obrazové informace |
| full_dept |
Department of Image Processing |
| department (cz) |
ZOI |
| department |
ZOI |
| full_dept |
Department of Image Processing |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0283562 |
| name1 |
Novozámský |
| name2 |
Adam |
| institution |
UTIA-B |
| full_dept (cz) |
Zpracování obrazové informace |
| full_dept |
Department of Image Processing |
| department (cz) |
ZOI |
| department |
ZOI |
| full_dept |
Department of Image Processing |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0101087 |
| name1 |
Flusser |
| name2 |
Jan |
| institution |
UTIA-B |
| full_dept (cz) |
Zpracování obrazové informace |
| full_dept |
Department of Image Processing |
| department (cz) |
ZOI |
| department |
ZOI |
| full_dept |
Department of Image Processing |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| project_id |
GA21-03921S |
| agency |
GA ČR |
| ARLID |
cav_un_auth*0412209 |
|
| project |
| project_id |
StrategieAV21/1 |
| agency |
AV ČR |
| country |
CZ |
| ARLID |
cav_un_auth*0441412 |
|
| project |
|
| abstract
(eng) |
We introduce NeRD, a new demosaicking method for generating full-color images from Bayer patterns. Our approach leverages advancements in neural fields to perform demosaicking by representing an image as a coordinate-based neural network with sine activation functions. The inputs to the network are spatial coordinates and a low-resolution Bayer pattern, while the outputs are the corresponding RGB values. An encoder network, which is a blend of ResNet and U-net, enhances the implicit neural representation of the image to improve its quality and ensure spatial consistency through prior learning. Our experimental results demonstrate that NeRD outperforms traditional and state-of-the-art CNN-based methods and significantly closes the gap to transformer-based methods. |
| action |
| ARLID |
cav_un_auth*0455338 |
| name |
IEEE International Conference on Image Processing 2023 (ICIP 2023) |
| dates |
20231008 |
| mrcbC20-s |
20231011 |
| place |
Kuala Lumpur |
| country |
MY |
|
| RIV |
JC |
| FORD0 |
10000 |
| FORD1 |
10200 |
| FORD2 |
10201 |
| reportyear |
2024 |
| num_of_auth |
4 |
| presentation_type |
PR |
| inst_support |
RVO:67985556 |
| permalink |
https://hdl.handle.net/11104/0345842 |
| cooperation |
| ARLID |
cav_un_auth*0329918 |
| name |
FJFI ČVUT Praha |
| country |
CZ |
|
| confidential |
S |
| arlyear |
2023 |
| mrcbU14 |
SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
WOS |
| mrcbU63 |
cav_un_epca*0575755 Proceedings of the 2023 IEEE International Conference on Image Processing (ICIP) 978-1-7281-9835-4 1735 1739 Piscataway IEEE 2023 |
|