Name
Abstract | ||
|---|---|---|
Even though the study of saliency for color images has been thoroughly investigated in the past, very little attention has
been given to datasets that cannot be displayed on traditional computer screens such as spectral images. Nevertheless, more
than a means to predict human gaze, the study of saliency primarily allows for measuring informative content. Thus, we propose
a novel approach for the computation of saliency maps for spectral images. Based on the Itti model, it involves the extraction of both spatial and spectral features, suitable for high dimensionality images. As an application,
we present a comparison framework to evaluate how dimensionality reduction techniques convey information from the initial
image. Results on two datasets prove the efficiency and the relevance of the proposed approach.
|
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-21227-7_11 | Scandinavian Conference on Image Analysis |
Keywords | Field | DocType |
novel approach,high dimensionality image,itti model,color image,dimensionality reduction technique,spectral feature,spectral image,comparison framework,saliency map,information content,spectral imaging | Computer vision,Dimensionality reduction,Gaze,Kadir–Brady saliency detector,Pattern recognition,Computer science,Salience (neuroscience),Curse of dimensionality,Visual attention,Artificial intelligence,Computation | Conference |
Volume | ISSN | Citations |
6688 | 0302-9743 | 2 |
PageRank | References | Authors |
0.45 | 11 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Steven Le Moan | 1 | 46 | 10.80 |
| Alamin Mansouri | 2 | 137 | 22.29 |
| Jon Yngve Hardeberg | 3 | 365 | 59.20 |
| Yvon Voisin | 4 | 65 | 12.66 |