| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0450671 |
| utime |
20240103211222.2 |
| mtime |
20151120235959.9 |
| SCOPUS |
84925617936 |
| WOS |
000353135300007 |
| DOI |
10.1117/12.2077158 |
| title
(primary) (eng) |
Blind deconvolution of images with model discrepancies using maximum a posteriori estimation with heavy-tailed priors |
| specification |
| page_count |
12 s. |
| media_type |
C |
|
| serial |
| ARLID |
cav_un_epca*0445084 |
| ISBN |
978-1-62841-494-3 |
| ISSN |
0277-786X |
| title
|
Digital Photography XI |
| publisher |
| place |
Bellingham |
| name |
SPIE-IS&T |
| year |
2015 |
|
|
| keyword |
image blind deconvolution |
| keyword |
image deblurring |
| keyword |
blur estimation |
| keyword |
pixel saturation |
| keyword |
boundary artifacts |
| author
(primary) |
| ARLID |
cav_un_auth*0293863 |
| name1 |
Kotera |
| name2 |
Jan |
| full_dept (cz) |
Zpracování obrazové informace |
| full_dept (eng) |
Department of Image Processing |
| department (cz) |
ZOI |
| department (eng) |
ZOI |
| institution |
UTIA-B |
| full_dept |
Department of Image Processing |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0101209 |
| name1 |
Šroubek |
| name2 |
Filip |
| full_dept (cz) |
Zpracování obrazové informace |
| full_dept |
Department of Image Processing |
| department (cz) |
ZOI |
| department |
ZOI |
| institution |
UTIA-B |
| full_dept |
Department of Image Processing |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| project_id |
938213/2013 |
| agency |
GA UK |
| country |
CZ |
| ARLID |
cav_un_auth*0302211 |
|
| project |
| project_id |
M100751201 |
| agency |
GA AV ČR |
| country |
CZ |
| ARLID |
cav_un_auth*0289164 |
|
| abstract
(eng) |
Single image blind deconvolution aims to estimate the unknown blur from a single observed blurred image and recover the original sharp image. Such task is severely ill-posed and typical approaches involve some heuristic or other steps without clear mathematical explanation to arrive at an acceptable solution. We show that a straight- forward maximum a posteriori estimation incorporating sparse priors and mechanism to deal with boundary artifacts, combined with an efficient numerical method can produce results which compete with or outperform much more complicated state-of-the-art methods. Our method is naturally extended to deal with overexposure in low-light photography, where linear blurring model is violated. |
| action |
| ARLID |
cav_un_auth*0316974 |
| name |
Digital Photography and Mobile Imaging XI |
| place |
San Francisco |
| dates |
09.02.2015-10.02.2015 |
| country |
US |
|
| reportyear |
2016 |
| RIV |
JD |
| num_of_auth |
2 |
| presentation_type |
PR |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0251952 |
| mrcbC61 |
1 |
| confidential |
S |
| mrcbT16-s |
0.223 |
| mrcbT16-E |
Q4 |
| arlyear |
2015 |
| mrcbU14 |
84925617936 SCOPUS |
| mrcbU34 |
000353135300007 WOS |
| mrcbU63 |
cav_un_epca*0445084 Digital Photography XI 978-1-62841-494-3 0277-786X 94040B Bellingham SPIE-IS&T 2015 SPIE Proceedings 9404 |
|