Name
Abstract | ||
|---|---|---|
In recent years, several image fusion techniques have been proposed to cater to various objectives. An appropriate visualization of the data is one of the key objectives of image fusion, particularly in case of hyperspectral images where the number of bands are far more than those can be displayed on standard tristimulus display. While a few techniques that address the issue of visualization of hyperspectral data can be seen in the literature, the evaluation of performances of these different techniques is still an open problem. In this paper, we first introduce a notion called fusion consistency and we suggest that the fusion techniques should satisfy the consistency criterion under appropriate measures that evaluate the fusion performance. We also propose several modifications for a number of existing measures that can quantify the progression of fusion operation efficiently for the fusion of a large number of image bands. We use these observations to validate suitability of any given technique for fusion of hyperspectral images. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1016/j.inffus.2011.03.008 | Information Fusion |
Keywords | Field | DocType |
fusion consistency,performance evaluation,image fusion,image quality assessment,quantitative evaluation,fusion technique,hyperspectral image fusion technique,novel approach,fusion performance,fusion operation,hyperspectral data,hyperspectral image fusion,image band,large number,image fusion technique,hyperspectral image | Data mining,Open problem,Image fusion,Pattern recognition,Consistency criterion,Visualization,Fusion,Hyperspectral imaging,Artificial intelligence,Mathematics | Journal |
Volume | Issue | ISSN |
14 | 1 | Information Fusion |
Citations | PageRank | References |
15 | 0.71 | 26 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ketan Kotwal | 1 | 65 | 3.49 |
| Subhasis Chaudhuri | 2 | 1384 | 133.18 |