| bibtype |
J -
Journal Article
|
| ARLID |
0563455 |
| utime |
20230323094921.7 |
| mtime |
20221104235959.9 |
| SCOPUS |
85135316166 |
| WOS |
000859686100008 |
| DOI |
10.1016/j.eswa.2022.118272 |
| title
(primary) (eng) |
A feature level image fusion for Night-Vision context enhancement using Arithmetic optimization algorithm based image segmentation |
| specification |
| page_count |
14 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0252943 |
| ISSN |
0957-4174 |
| title
|
Expert Systems With Applications |
| volume_id |
209 |
| publisher |
|
|
| keyword |
infrared (IR) |
| keyword |
visible image |
| keyword |
image fusion |
| keyword |
AOA |
| keyword |
image segmentation |
| keyword |
WLS |
| author
(primary) |
| ARLID |
cav_un_auth*0439238 |
| name1 |
Singh |
| name2 |
S. |
| country |
IN |
|
| author
|
| ARLID |
cav_un_auth*0439239 |
| name1 |
Singh |
| name2 |
H. |
| country |
IN |
|
| author
|
| ARLID |
cav_un_auth*0439240 |
| name1 |
Mittal |
| name2 |
N. |
| country |
IN |
|
| author
|
| ARLID |
cav_un_auth*0439241 |
| name1 |
Singh |
| name2 |
H. |
| country |
IN |
|
| author
|
| ARLID |
cav_un_auth*0439242 |
| name1 |
Hussien |
| name2 |
A.G. |
| country |
EG |
|
| author
|
| ARLID |
cav_un_auth*0101209 |
| name1 |
Šroubek |
| name2 |
Filip |
| institution |
UTIA-B |
| full_dept (cz) |
Zpracování obrazové informace |
| full_dept |
Department of Image Processing |
| department (cz) |
ZOI |
| department |
ZOI |
| full_dept |
Department of Image Processing |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| source |
|
| cas_special |
| abstract
(eng) |
Images are fused to produce a composite image by combining key characteristics of the source images in image fusion. It makes the fused image better for human vision and machine vision. A novel procedure of Infrared (IR) and Visible (Vis) image fusion is proposed in this manuscript. The main challenges of feature level image fusion are that it will introduce artifacts and noise in the fused image. To preserve the meaningful information without adding artifacts from the source input images, weight map computed from Arithmetic optimization algorithm (AOA) is used for the image fusion process. In this manuscript, feature level fusion is performed after refining the weight maps using a weighted least square optimization (WLS) technique. Through this, the derived salient object details are merged into the visual image without introducing distortion. To affirm the validity of the proposed methodology simulation results are carried for twenty-one image data sets. It is concluded from the qualitative and quantitative experimental analysis that the proposed method works well for most of the image data sets and shows better performance than certain traditional existing models. |
| result_subspec |
WOS |
| RIV |
JD |
| FORD0 |
20000 |
| FORD1 |
20200 |
| FORD2 |
20204 |
| reportyear |
2023 |
| num_of_auth |
6 |
| inst_support |
RVO:67985556 |
| permalink |
https://hdl.handle.net/11104/0336403 |
| confidential |
S |
| article_num |
118272 |
| mrcbC86 |
1* Article Computer Science Artificial Intelligence|Engineering Electrical Electronic|Operations Research Management Science |
| mrcbC91 |
C |
| mrcbT16-e |
COMPUTERSCIENCEARTIFICIALINTELLIGENCE|ENGINEERINGELECTRICALELECTRONIC|OPERATIONSRESEARCHMANAGEMENTSCIENCE |
| mrcbT16-j |
1.277 |
| mrcbT16-s |
1.873 |
| mrcbT16-D |
Q2 |
| mrcbT16-E |
Q1 |
| arlyear |
2022 |
| mrcbU14 |
85135316166 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
000859686100008 WOS |
| mrcbU63 |
cav_un_epca*0252943 Expert Systems With Applications 0957-4174 1873-6793 Roč. 209 č. 1 2022 Elsevier |
|