| bibtype |
J -
Journal Article
|
| ARLID |
0559599 |
| utime |
20240903204336.3 |
| mtime |
20220802235959.9 |
| SCOPUS |
85135334269 |
| WOS |
000827936600001 |
| DOI |
10.5201/ipol.2022.385 |
| title
(primary) (eng) |
Spectral Pre-Adaptation for Restoring Real-World Blurred Images using Standard Deconvolution Methods |
| specification |
| page_count |
29 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0559598 |
| ISSN |
2105-1232 |
| title
|
Image Processing On Line |
| volume_id |
12 |
| volume |
1 (2022) |
| page_num |
218-246 |
| publisher |
|
|
| keyword |
image restoration |
| keyword |
non-circulant deconvolution |
| keyword |
maximum likelihood interpolation |
| keyword |
model discrepancies |
| keyword |
missing samples |
| author
(primary) |
| ARLID |
cav_un_auth*0433868 |
| name1 |
Dong |
| name2 |
Ch. |
| country |
SG |
|
| 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*0433869 |
| name1 |
Portilla |
| name2 |
J. |
| country |
ES |
|
| source |
|
| source |
|
| cas_special |
| project |
| project_id |
GA20-27939S |
| agency |
GA ČR |
| ARLID |
cav_un_auth*0391986 |
|
| abstract
(eng) |
We present spectral pre-adaptation that pre-processes blurred images so they can be restored using fast standard deconvolution algorithms suitable for simplified models. |
| result_subspec |
WOS |
| RIV |
JD |
| FORD0 |
10000 |
| FORD1 |
10200 |
| FORD2 |
10201 |
| reportyear |
2023 |
| num_of_auth |
3 |
| inst_support |
RVO:67985556 |
| permalink |
https://hdl.handle.net/11104/0333417 |
| confidential |
S |
| mrcbC86 |
3+4 Article Computer Science Software Engineering |
| mrcbC91 |
A |
| mrcbT16-e |
COMPUTERSCIENCE.SOFTWAREENGINEERING |
| mrcbT16-f |
1.5 |
| mrcbT16-g |
0.3 |
| mrcbT16-h |
9.8 |
| mrcbT16-i |
0.00032 |
| mrcbT16-j |
0.397 |
| mrcbT16-k |
741 |
| mrcbT16-s |
0.348 |
| mrcbT16-5 |
1.000 |
| mrcbT16-6 |
18 |
| mrcbT16-E |
Q4 |
| mrcbT16-M |
0.36 |
| mrcbT16-N |
Q4 |
| arlyear |
2022 |
| mrcbU14 |
85135334269 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
000827936600001 WOS |
| mrcbU56 |
pdf 5MB |
| mrcbU63 |
cav_un_epca*0559598 Image Processing On Line 2105-1232 2105-1232 Roč. 12 č. 1 2022 218 246 IPOL |
|