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Multi-operator Image Retargeting with Preserving Aspect Ratio of Important Contents

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Advances in Multimedia Information Processing – PCM 2017 (PCM 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10736))

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Abstract

Content-aware image retargeting can preserve the quality of visually important objects during image resizing. However, some previous approaches fail to provide desired results as the sizes of the important objects in original images are larger than the target resolution of resized images. In this paper, we propose a novel multi-operator image retargeting scheme, which combines seam carving (SC) methods with uniform scaling techniques. To guarantee the quality of visually important objects, we stretch original images in both vertical and horizontal directions and then perform similarity transformation by using the indirect SC and uniform scaling methods. Besides, the direct SC method with gradient vector flow (GVF) is also employed to shrink the image finally. Experiments demonstrated that the proposed scheme could produce more desirable resized images than the existing methods.

This work was supported in part by the National Natural Science Foundation of China (Nos. 61461006, 61401108) and the Guangxi Natural Science Foundation Project (No. 2016GXNSFAA380216).

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Author information

Authors and Affiliations

  1. School of Computer and Electronic Information, Guangxi University, Nanning, China

    Qian Zhang, Zhenhua Tang & Kan Chang

  2. Guangxi Key Laboratory of Multimedia Communications and Network Technology, Guangxi University, Nanning, China

    Zhenhua Tang & Kan Chang

  3. School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, China

    Hongbo Jiang

Authors
  1. Qian Zhang
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  2. Zhenhua Tang
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  3. Hongbo Jiang
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  4. Kan Chang
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Corresponding author

Correspondence to Zhenhua Tang .

Editor information

Editors and Affiliations

  1. University of Electronic Science and Technology of China, Chengdu, China

    Bing Zeng

  2. University of Chinese Academy of Sciences, Beijing, China

    Qingming Huang

  3. University of Ottawa, Ottawa, Ontario, Canada

    Abdulmotaleb El Saddik

  4. University of Electronic Science and Technology of China, Chengdu, China

    Hongliang Li

  5. Chinese Academy of Sciences, Beijing, China

    Shuqiang Jiang

  6. Harbin Institute of Technology, Harbin, China

    Xiaopeng Fan

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Zhang, Q., Tang, Z., Jiang, H., Chang, K. (2018). Multi-operator Image Retargeting with Preserving Aspect Ratio of Important Contents. In: Zeng, B., Huang, Q., El Saddik, A., Li, H., Jiang, S., Fan, X. (eds) Advances in Multimedia Information Processing – PCM 2017. PCM 2017. Lecture Notes in Computer Science(), vol 10736. Springer, Cham. https://doi.org/10.1007/978-3-319-77383-4_30

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  • DOI: https://doi.org/10.1007/978-3-319-77383-4_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-77382-7

  • Online ISBN: 978-3-319-77383-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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