Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/50583
Title: Algorithms for image saliency via sparse representation and multi-scale inputs image retargeting
Authors: Hoang, Minh Chau
Keywords: DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Issue Date: 2011
Source: Hoang, M. C. (2011). Algorithms for image saliency via sparse representation and multi-scale inputs image retargeting.Master’s thesis, Nanyang Technological University, Singapore.
Abstract: Saliency detection is an important yet challenging task in computer vision. In this report we investigate the use of sparse coding over redundant dictionary for saliency detection. We attempt to present a small fraction of the growing knowledge regarding sparse representation over redundant dictionary and discuss some potential usage of this powerful tool for saliency detection task. We propose a new algorithm for saliency detection based on the likelihood that images patch can be encoded sparsely using a dictionary learned from other patches. Experimental results based on saliency ground of truth of 1000 real images shows a superior performance of the renew algorithm in comparison with other existing saliency algorithms.
URI: https://hdl.handle.net/10356/50583
DOI: 10.32657/10356/50583
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Theses

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