| bibtype |
A -
Abstract
|
| ARLID |
0467530 |
| utime |
20240103213204.5 |
| mtime |
20161219235959.9 |
| title
(primary) (eng) |
HANDLING BLUR (Tutorial) |
| specification |
| page_count |
3 |
| media_type |
E |
|
| serial |
| ARLID |
cav_un_epca*0467529 |
| title
|
Proceedings of the 23rd International Conference on Pattern Recognition |
| publisher |
| place |
Cancun |
| name |
IAPR |
| year |
2016 |
|
|
| keyword |
Blur |
| keyword |
image restoration |
| keyword |
image analysis |
| author
(primary) |
| ARLID |
cav_un_auth*0101087 |
| name1 |
Flusser |
| 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. |
|
| author
|
| ARLID |
cav_un_auth*0101238 |
| name1 |
Zitová |
| name2 |
Barbara |
| 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 |
| ARLID |
cav_un_auth*0314467 |
| project_id |
GA15-16928S |
| agency |
GA ČR |
|
| abstract
(eng) |
Blur is an inevitable unwanted phenomenon, which is present in all digital images. It results in smoothing high-frequency details, which makes the image analysis difficult. Heavy blur may degrade the image so seriously, that neither automatic analysis nor visual interpretation of the content are possible. If we did not have proper tools for processing and analyzing blurred images, many unique images would become useless. Two major approaches to handling blurred images exist. They are more complementary rather than concurrent; each of them is appropriate for different tasks and employs different mathematical methods and algorithms. |
| action |
| ARLID |
cav_un_auth*0339744 |
| name |
International Conference on Pattern Recognition 2016 /23./ |
| dates |
20161204 |
| place |
Cancun |
| country |
MX |
| mrcbC20-s |
20161208 |
|
| RIV |
JD |
| reportyear |
2017 |
| num_of_auth |
3 |
| mrcbC52 |
4 O 4o 20231122142122.4 |
| presentation_type |
ZP |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0265624 |
| mrcbC61 |
1 |
| confidential |
S |
| arlyear |
2016 |
| mrcbTft |
\nSoubory v repozitáři: 0467530.pdf |
| mrcbU14 |
SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
WOS |
| mrcbU63 |
cav_un_epca*0467529 Proceedings of the 23rd International Conference on Pattern Recognition Cancun IAPR 2016 |
|