bibtype |
C -
Conference Paper (international conference)
|
ARLID |
0313521 |
utime |
20240111140708.1 |
mtime |
20081029235959.9 |
title
(primary) (eng) |
Texture Oriented Image Inpainting based on Local Statistical Model |
specification |
page_count |
6 s. |
media_type |
CD-ROM |
|
serial |
ARLID |
cav_un_epca*0313520 |
title
|
Proc. 10th IASTED Conf. on Signal & Image Processing, SIP 2008 |
page_num |
15-20 |
publisher |
place |
Calgary |
name |
ACTA Press |
year |
2008 |
|
editor |
|
|
title
(cze) |
Texturně orientovaná metoda obrazového vkreslování založená na lokálním statistickém modelu |
keyword |
Image Restoration |
keyword |
Image Inpainting |
keyword |
Color Texture Prediction |
keyword |
Local Texture Model |
keyword |
Gaussian Mixtures |
keyword |
EM Algorithm |
author
(primary) |
ARLID |
cav_un_auth*0101091 |
name1 |
Grim |
name2 |
Jiří |
institution |
UTIA-B |
full_dept |
Department of Pattern Recognition |
fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
author
|
ARLID |
cav_un_auth*0101197 |
name1 |
Somol |
name2 |
Petr |
institution |
UTIA-B |
full_dept |
Department of Pattern Recognition |
fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
author
|
ARLID |
cav_un_auth*0101182 |
name1 |
Pudil |
name2 |
Pavel |
institution |
UTIA-B |
full_dept |
Department of Pattern Recognition |
fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
author
|
ARLID |
cav_un_auth*0243189 |
name1 |
Míková |
name2 |
I. |
country |
CZ |
|
author
|
ARLID |
cav_un_auth*0231129 |
name1 |
Malec |
name2 |
M. |
country |
CZ |
|
source |
|
cas_special |
project |
project_id |
1M0572 |
agency |
GA MŠk |
ARLID |
cav_un_auth*0001814 |
|
project |
project_id |
2C06019 |
agency |
GA MŠk |
country |
CZ |
ARLID |
cav_un_auth*0216518 |
|
project |
project_id |
GA102/08/0593 |
agency |
GA ČR |
ARLID |
cav_un_auth*0239567 |
|
project |
project_id |
GA102/07/1594 |
agency |
GA ČR |
ARLID |
cav_un_auth*0228611 |
|
research |
CEZ:AV0Z10750506 |
abstract
(eng) |
Image inpainting as a means of substituting missing image parts can become difficult when the image is textured. In this paper we apply a local statistical model of the source color image with the aim to predict missing texture regions. We have shown in a series of papers that textures can be modeled locally by estimating the joint probability density of spectral pixel values in a suitably chosen observation window. For the sake of image inpainting we estimate the joint multivariate density in the form of a Gaussian mixture of product components. The missing image region is inpainted iteratively by step-wise prediction of the unknown spectral values. |
abstract
(cze) |
Obrazové vkreslování (automatické nahrazování chybějících částí obrazu) je obzvláště obtížné v případě texturních obrázků. Aplikujeme lokální statistický model využívající posuvného okna, který umožňuje rekonstruovat texturní vlastnosti. Pro účely vkreslování odhadujeme vícerozměrnou hustotu ve formě gausovské směsi součinových komponent. Chybějící části obrazu jsou vkreslovány iterativně. |
action |
ARLID |
cav_un_auth*0243073 |
name |
10th IASTED Conf. on Signal & Image Processing, SIP 2008 |
place |
Kailua-Kona, HI |
dates |
18.08.2008-20.08.2008 |
country |
US |
|
reportyear |
2009 |
RIV |
BD |
permalink |
http://hdl.handle.net/11104/0164319 |
arlyear |
2008 |
mrcbU56 |
pdf |
mrcbU63 |
cav_un_epca*0313520 Proc. 10th IASTED Conf. on Signal & Image Processing, SIP 2008 15 20 Calgary ACTA Press 2008 |
mrcbU67 |
Cristea P. 340 |
|