Conference paper
Bottom-up visual saliency map using wavelet transform domain
2010 3rd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2010, pp.692-695
International Conference on Computer Science and Information Technology (ICCSIT), 3rd (Chengdu, China, 09-Jul-2010–11-Jul-2010)
Institute of Electrical and Electronics Engineers
2010
Abstract
Object or region based image processing can be performed more efficiently with information pertaining locations that are visually salient to human perception with the aid of a saliency map. The saliency map is a master topological map having the possible locations of objects or regions which a human perceived as important/salient. In this paper, a method to compute the saliency map in the wavelet transform domain is explored. Previous works involving saliency in this domain usually involves salient points, which are in fact accurate but they do not cover the area as a region and involve heavy repeated iterations. The method explored in this paper is compared to two state-of-art methods in which these methods involve the frequency domain. The presented method provides more accurate salient regions compared to the other two methods while retaining a resolution which the salient regions are visually identifiable.
Details
- Title
- Bottom-up visual saliency map using wavelet transform domain
- Authors
- Christopher Wing Hong Ngau (Author) - University of Nottingham Malaysia CampusLi-Minn Ang (Author) - University of Nottingham Malaysia CampusKah Phooi Seng (Author) - University of Nottingham Malaysia Campus
- Publication details
- 2010 3rd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2010, pp.692-695
- Conference details
- International Conference on Computer Science and Information Technology (ICCSIT), 3rd (Chengdu, China, 09-Jul-2010–11-Jul-2010)
- Publisher
- Institute of Electrical and Electronics Engineers
- Date published
- 2010
- DOI
- 10.1109/ICCSIT.2010.5564545
- ISBN
- 9781424455409
- Organisation Unit
- University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering; Engage Research Lab
- Language
- English
- Record Identifier
- 99513901802621
- Output Type
- Conference paper
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