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Saliency detection using quaternionic distance based weber local descriptor and level priors

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Abstract

In this paper, a novel and efficient framework by exploiting Quaternionic Distance Based Weber Local Descriptor (QDWLD) and object cues is proposed for image saliency detection. In contrast to the existing saliency detection models, the advantage of the proposed approach is that it can combine quaternion number system and object cues simultaneously, which is independent of image contents and scenes. Firstly, QDWLD, which was initially designed for detecting outliers in color images, is used to represent the directional cues in an image. Meanwhile, two low-level priors, namely the Convex-Hull-Based center and color contrast cue of the image, are utilized and fused as an object-level cue. Finally, by combining QDWLD with object cues, a reliable saliency map of the image can be computed and estimated. Experimental results, based on two widely used and openly available database, show that the proposed method is able to produce reliable and promising salient maps/estimations, compared to other state-of-the-art saliency-detection models.

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Acknowledgements

We would like to thank Dr. Rushi Lan in the Faculty of Science and Technology, University of Macau for providing the QDWLD Matlab code.

This work was supported by National Natural Science Foundation of China (NSFC) (61601427, 61602229); Natural Science Foundation of Shandong Province (ZR2015FQ011); China Postdoctoral Science Foundation funded project (2016 M590659); Postdoctoral Science Foundation of Shandong Province (201603045); Qingdao Postdoctoral Science Foundation funded project (861605040008) and Applied Basic Research Project of Qingdao (16-5-1-4-jch); The Fundamental Research Funds for the Central Universities (201511008, 30020084851); & Technology Cooperation Program of China (ISTCP) (2014DFA10410).

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Authors and Affiliations

  1. School of Computer Science and Technology, Shandong University of Finance and Economics, Jinan, 250014, China

    Muwei Jian

  2. Department of Computer Science and Technology, Ocean University of China, Qingdao, 266100, China

    Muwei Jian, Qiang Qi, Junyu Dong & Xin Sun

  3. College of Information and Electrical Engineering, Ludong University, 186 Shixue Road, Yantai, 264025, China

    Yujuan Sun

  4. Centre for Signal Processing, Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong

    Kin-Man Lam

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  1. Muwei Jian
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  2. Qiang Qi
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  3. Junyu Dong
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  4. Xin Sun
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  5. Yujuan Sun
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Correspondence to Muwei Jian.

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Jian, M., Qi, Q., Dong, J. et al. Saliency detection using quaternionic distance based weber local descriptor and level priors. Multimed Tools Appl 77, 14343–14360 (2018). https://doi.org/10.1007/s11042-017-5032-z

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  • DOI: https://doi.org/10.1007/s11042-017-5032-z

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