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    Multi-spectral saliency detection

    Wang, Q. and Yan, P. and Yuan, Y. and Li, Xuelong (2013) Multi-spectral saliency detection. Pattern Recognition Letters 34 (1), pp. 34-41. ISSN 0167-8655.

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    Abstract

    Visual saliency detection has been applied in many tasks in the fields of pattern recognition and computer vision, such as image segmentation, object recognition, and image retargeting. However, the accurate detection of saliency remains a challenge. The reasons behind this are that: (1) well-defined mechanism for saliency definition is rarely established; and (2) supporting information for detecting saliency is limited in general. In this paper, a multi-spectrum based saliency detection algorithm is proposed. Instead of only using the conventional RGB information as what existing algorithms do, this work incorporates near-infrared clues into the detection framework. Features of color and texture from both types of image modes are explored simultaneously. When calculating the color contrast, an effective color component analysis method is employed to produce more precise results. With respect to the texture analysis, texton representation is adopted for fast processing. Experiments are done to compare the proposed algorithm with other 11 state-of-the-art algorithms and the results indicate that our algorithm outperforms the others.

    Metadata

    Item Type: Article
    Keyword(s) / Subject(s): saliency, near-infrared, multi-spectral, texton, color
    School: School of Business, Economics & Informatics > Computer Science and Information Systems
    Depositing User: Sarah Hall
    Date Deposited: 06 Jun 2013 10:27
    Last Modified: 11 Oct 2016 15:27
    URI: https://eprints.bbk.ac.uk/id/eprint/7299

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