| bibtype |
J -
Journal Article
|
| ARLID |
0366506 |
| utime |
20240103195753.4 |
| mtime |
20111110235959.9 |
| WOS |
000296016200010 |
| DOI |
10.1109/TIP.2011.2158227 |
| title
(primary) (eng) |
Image magnification using interval information |
| specification |
|
| serial |
| ARLID |
cav_un_epca*0253235 |
| ISSN |
1057-7149 |
| title
|
IEEE Transactions on Image Processing |
| volume_id |
20 |
| volume |
11 (2011) |
| page_num |
3112-3123 |
| publisher |
| name |
Institute of Electrical and Electronics Engineers |
|
|
| keyword |
image magnification |
| keyword |
implication operator |
| keyword |
interval |
| author
(primary) |
| ARLID |
cav_un_auth*0275667 |
| name1 |
Jurio |
| name2 |
A. |
| country |
ES |
|
| author
|
| ARLID |
cav_un_auth*0275753 |
| name1 |
Pagola |
| name2 |
M. |
| country |
ES |
|
| author
|
| ARLID |
cav_un_auth*0101163 |
| name1 |
Mesiar |
| name2 |
Radko |
| full_dept (cz) |
Ekonometrie |
| full_dept |
Department of Econometrics |
| department (cz) |
E |
| department |
E |
| institution |
UTIA-B |
| full_dept |
Department of Econometrics |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0262210 |
| name1 |
Beliakov |
| name2 |
G. |
| country |
AU |
|
| author
|
| ARLID |
cav_un_auth*0248954 |
| name1 |
Bustince |
| name2 |
H. |
| country |
ES |
|
| source |
|
| cas_special |
| project |
| project_id |
GAP402/11/0378 |
| agency |
GA ČR |
| ARLID |
cav_un_auth*0273630 |
|
| research |
CEZ:AV0Z10750506 |
| abstract
(eng) |
In this paper, a simple and effective image-magnification algorithm based on intervals is proposed. A low-resolution image is magnified to form a high-resolution image using a block-expanding method. Our proposed method associates each pixel with an interval obtained by a weighted aggregation of the pixels in its neighborhood. From the interval and with a linear K-alpha operator, we obtain the magnified image. Experimental results show that our algorithm provides a magnified image with better quality (peak signal-to-noise ratio) than several existing methods. |
| reportyear |
2013 |
| RIV |
BA |
| num_of_auth |
5 |
| permalink |
http://hdl.handle.net/11104/0201478 |
| mrcbT16-e |
COMPUTERSCIENCEARTIFICIALINTELLIGENCE|ENGINEERINGELECTRICALELECTRONIC |
| mrcbT16-f |
3.770 |
| mrcbT16-g |
0.378 |
| mrcbT16-h |
7.3 |
| mrcbT16-i |
0.03717 |
| mrcbT16-j |
1.61 |
| mrcbT16-k |
12063 |
| mrcbT16-l |
296 |
| mrcbT16-q |
156 |
| mrcbT16-s |
1.516 |
| mrcbT16-y |
34.77 |
| mrcbT16-x |
4.83 |
| mrcbT16-4 |
Q1 |
| mrcbT16-B |
94.768 |
| mrcbT16-C |
92.107 |
| mrcbT16-D |
Q1* |
| mrcbT16-E |
Q2 |
| arlyear |
2011 |
| mrcbU34 |
000296016200010 WOS |
| mrcbU63 |
cav_un_epca*0253235 IEEE Transactions on Image Processing 1057-7149 1941-0042 Roč. 20 č. 11 2011 3112 3123 Institute of Electrical and Electronics Engineers |
|