Name
Abstract | ||
|---|---|---|
The aim of image fusion is to combine information from multiple images of the same scene. The result of image fusion is a new image,,which is more suitable for human and machine perception or further image-processing tasks such as segmentation, feature extraction and object recognition. Different fusion methods have been proposed in the literature. This paper presents new methods based on the computation of local and global gradient. A comparative analysis is carried out against other existing strategies. The results are encouraging. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1007/978-3-540-44871-6_106 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
feature extraction,object recognition,image fusion,image processing,comparative analysis | Computer vision,Machine perception,Feature detection (computer vision),Pattern recognition,Image fusion,Computer science,Segmentation,Image processing,Sensor fusion,Feature extraction,Artificial intelligence,Cognitive neuroscience of visual object recognition | Conference |
Volume | ISSN | Citations |
2652 | 0302-9743 | 5 |
PageRank | References | Authors |
1.15 | 4 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Matilde Santos | 1 | 143 | 24.39 |
| Gonzalo Pajares | 2 | 699 | 57.18 |
| M. Portela | 3 | 5 | 1.15 |
| Jesús Manuel De La Cruz | 4 | 373 | 25.35 |