| bibtype |
A -
Abstract
|
| ARLID |
0423186 |
| utime |
20240103203700.5 |
| mtime |
20140207235959.9 |
| title
(primary) (eng) |
Fast algorithms for Bayesian JPEG decompression |
| specification |
|
| serial |
| ARLID |
cav_un_epca*0424930 |
| title
|
Proceedings of the 3rd SPLab Workshop 2013 |
| publisher |
| place |
Brno |
| name |
Signal Processing Laboratory |
| year |
2013 |
|
|
| keyword |
JPEG decompression |
| keyword |
image restoration |
| keyword |
image processing |
| author
(primary) |
| ARLID |
cav_un_auth*0108377 |
| name1 |
Šorel |
| name2 |
Michal |
| 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. |
|
| cas_special |
| abstract
(eng) |
JPEG decompression can be formulated as a probabilistic problem and solved in the standard way using the Bayesian approach. The choice of image prior probability distribution influences complexity of the corresponding minimization problem. In this talk we show how a convenient form of this prior allows for efficient solution by a primal-dual method. |
| action |
| ARLID |
cav_un_auth*0299361 |
| name |
3rd SPLab Workshop 2013 |
| place |
Brno |
| dates |
2013 |
| country |
CZ |
|
| reportyear |
2014 |
| RIV |
JD |
| presentation_type |
ZP |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0230916 |
| confidential |
S |
| arlyear |
2013 |
| mrcbU63 |
cav_un_epca*0424930 Proceedings of the 3rd SPLab Workshop 2013 Brno Signal Processing Laboratory 2013 |
|