bibtype |
J -
Journal Article
|
ARLID |
0424586 |
utime |
20240111140844.1 |
mtime |
20140207235959.9 |
WOS |
000331892700055 |
SCOPUS |
84897748145 |
DOI |
10.1117/1.JBO.19.1.016023 |
title
(primary) (eng) |
Restoration of retinal images with space-variant blur |
specification |
page_count |
12 s. |
media_type |
P |
|
serial |
ARLID |
cav_un_epca*0255934 |
ISSN |
1083-3668 |
title
|
Journal of Biomedical Optics |
volume_id |
19 |
volume |
1 (2014) |
|
keyword |
blind deconvolution |
keyword |
space-variant restoration |
keyword |
retinal image |
author
(primary) |
ARLID |
cav_un_auth*0275488 |
name1 |
Marrugo |
name2 |
A. |
country |
ES |
|
author
|
ARLID |
cav_un_auth*0278222 |
name1 |
Millán |
name2 |
M. S. |
country |
ES |
|
author
|
ARLID |
cav_un_auth*0108377 |
name1 |
Šorel |
name2 |
Michal |
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*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 |
GA13-29225S |
agency |
GA ČR |
ARLID |
cav_un_auth*0292734 |
|
abstract
(eng) |
Retinal images are essential clinical resources for the diagnosis of retinopathy and many other ocular diseases. Because of improper acquisition conditions or inherent optical aberrations in the eye, the images are often degraded with blur. In many common cases, the blur varies across the field of view. Most image deblurring algorithms assume a space-invariant blur, which fails in the presence of space-variant (SV) blur. In this work, we propose an innovative strategy for the restoration of retinal images in which we consider the blur to be both unknown and SV. We model the blur by a linear operation interpreted as a convolution with a point-spread function (PSF) that changes with the position in the image. To achieve an artifact-free restoration, we propose a framework for a robust estimation of the SV PSF based on an eye-domain knowledge strategy. The restoration method was tested on artificially and naturally degraded retinal images. The results show an important enhance- ment, significant enough to leverage the images’ clinical use |
reportyear |
2015 |
RIV |
JD |
mrcbC52 |
4 A 4a 20231122140101.3 |
inst_support |
RVO:67985556 |
permalink |
http://hdl.handle.net/11104/0230917 |
confidential |
S |
mrcbT16-e |
BIOCHEMICALRESEARCHMETHODS|OPTICS|RADIOLOGYNUCLEARMEDICINEMEDICALIMAGING |
mrcbT16-j |
0.762 |
mrcbT16-s |
1.324 |
mrcbT16-4 |
Q1 |
mrcbT16-B |
50.518 |
mrcbT16-C |
74.208 |
mrcbT16-D |
Q2 |
mrcbT16-E |
Q2 |
arlyear |
2014 |
mrcbTft |
\nSoubory v repozitáři: sorel-0424586.pdf |
mrcbU14 |
84897748145 SCOPUS |
mrcbU34 |
000331892700055 WOS |
mrcbU56 |
5.8MB |
mrcbU63 |
cav_un_epca*0255934 Journal of Biomedical Optics 1083-3668 1560-2281 Roč. 19 č. 1 2014 , 016023-1-016023-12 |
|