| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0446068 |
| utime |
20240103210319.7 |
| mtime |
20150806235959.9 |
| SCOPUS |
84960892963 |
| WOS |
000380472300003 |
| DOI |
10.1109/ICCIS.2015.7274540 |
| title
(primary) (eng) |
Color Texture Restoration |
| specification |
| page_count |
6 s. |
| media_type |
E |
|
| serial |
| ARLID |
cav_un_epca*0446067 |
| ISBN |
978-1-4673-7337-1 |
| title
|
IEEE 7th International Conferences on Cybernetics and Intelligent Systems (CIS), and Robotics, Automation and Mechatronics (RAM) |
| part_title |
CIS |
| page_num |
13-18 |
| publisher |
| place |
445 Hoes Lane, Piscataway, NJ 08854, USA |
| name |
IEEE |
| year |
2015 |
|
|
| keyword |
Texture restoration |
| keyword |
Gaussian mixture model |
| author
(primary) |
| ARLID |
cav_un_auth*0101093 |
| full_dept (cz) |
Rozpoznávání obrazu |
| full_dept (eng) |
Department of Pattern Recognition |
| department (cz) |
RO |
| department (eng) |
RO |
| full_dept |
Department of Pattern Recognition |
| name1 |
Haindl |
| name2 |
Michal |
| institution |
UTIA-B |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0101100 |
| full_dept (cz) |
Rozpoznávání obrazu |
| full_dept |
Department of Pattern Recognition |
| department (cz) |
RO |
| department |
RO |
| full_dept |
Department of Pattern Recognition |
| name1 |
Havlíček |
| name2 |
Vojtěch |
| institution |
UTIA-B |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| ARLID |
cav_un_auth*0303439 |
| project_id |
GA14-10911S |
| agency |
GA ČR |
| country |
CZ |
|
| abstract
(eng) |
Visual texture restoration strives not necessarily to recover the exact pixel-wise correspondence with some original unobservable texture but rather a texture which is visually indiscernible from the original one. This differs from the standard image restoration objective so it can consequently lead to different restoration techniques. A novel multispectral texture restoration method, capable to reduce simultaneously additive noise and to restore missing textural parts is presented. The restoration method is based on a descriptive, unusually complex, three-dimensional, spatial Gaussian mixture model. The model is inherently multispectral thus it does not suffer with the spectral quality compromises of the most alternative approaches. |
| action |
| ARLID |
cav_un_auth*0318307 |
| name |
7th IEEE International Conferences on Cybernetics and Intelligent Systems (CIS), and Robotics, Automation and Mechatronics (RAM) |
| dates |
17.07.2015-17.07.2015 |
| place |
Siem Reap |
| country |
KH |
|
| RIV |
BD |
| reportyear |
2016 |
| num_of_auth |
2 |
| presentation_type |
PR |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0248313 |
| confidential |
S |
| arlyear |
2015 |
| mrcbU14 |
84960892963 SCOPUS |
| mrcbU34 |
000380472300003 WOS |
| mrcbU63 |
cav_un_epca*0446067 IEEE 7th International Conferences on Cybernetics and Intelligent Systems (CIS), and Robotics, Automation and Mechatronics (RAM) CIS 978-1-4673-7337-1 13 18 445 Hoes Lane, Piscataway, NJ 08854, USA IEEE 2015 |
|