Name
Abstract | ||
|---|---|---|
This paper presents a simple and effective method to compute the pixel saliency with full resolution in an image. First, the proposed method creates an image representation of four color channels through the modified computation on the basis of Itti et al.[5]. Then the most informative channel is automatically identified from the derived four color channels. Finally, the pixel saliency is computed through the simple combination of contrast feature and spatial attention function on the individual channel. The proposed method is computationally very simple, but it achieves a very good performance in the comparison experiments with six other saliency detection methods. On the challenging database with 1,000 images, it outperforms six other methods in both identifying salient pixels and segmenting salient regions. |
Year | Venue | Keywords |
|---|---|---|
2012 | ICPR | image representation,image resolution,saliency detection approach,image segmentation,color channel,spatial attention function,salient region segmentation,contrast feature,salient pixel identification,image colour analysis |
Field | DocType | ISSN |
Computer vision,Feature detection (computer vision),Pattern recognition,Computer science,Range segmentation,Binary image,Image segmentation,Pixel,Artificial intelligence,Morphological gradient,Channel (digital image),Color image | Conference | 1051-4651 |
ISBN | Citations | PageRank |
978-1-4673-2216-4 | 1 | 0.35 |
References | Authors | |
7 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hui Zhang | 1 | 3 | 1.73 |
| Weiqiang Wang | 2 | 469 | 49.23 |
| Guiping Su | 3 | 13 | 2.36 |
| Lijuan Duan | 4 | 215 | 26.13 |