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Retargeted Image Quality Assessment: Current Progresses and Future Trends

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Visual Signal Quality Assessment

Abstract

The diversity and versatility of the display devices have imposed new demands on digital image processing. Variant devices of different resolution screens need to display the same image for human visual experience. The retargeting methods are proposed to adapt the source image into arbitrary sizes and simultaneously keep the salient content of the source signal of high visual quality. Therefore, there is a new challenge of objectively evaluating the retargeted image perceptual quality, where variant resolutions may be presented, the objective shape may be distorted, and some content information may be discarded. In this chapter, recent progresses in quality assessment of retargeted images are reviewed. Firstly, we will review and discuss the recently developed retargeting methods for images. Afterwards, the subjective approaches to assess the retargeted image are reviewed, as well as the constructed subjective databases. Thirdly, some objective quality metrics developed recently are reviewed and compared based on the databases. Finally, future trends are discussed on retargeted image quality assessment in terms of both subjective and objective approaches.

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Notes

  1. 1.

    http://people.csail.mit.edu/mrub/retargetme/survey/index.php?mode=0.

  2. 2.

    http://www.cs.bilkent.edu.tr/~bilmdg/bilvideo-7/Software.html.

  3. 3.

    http://www.seas.upenn.edu/~ofirpele/FastEMD/.

  4. 4.

    http://people.csail.mit.edu/torralba/code/spatialenvelope/.

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Acknowledgements

The work described in this chapter was partially supported by a grant from the Research Grants Council of the Hong Kong SAR, China (Project CUHK 415913); the National Nature Science Foundation of China under Grant No. 61301090; the ROSE Lab grant from the Singapore National Research Foundation; the Supporting Program for Beijing Excellent Talents under Grant No. 2013D009011000001, and the National Natural Science Foundation of China under Grant No. 61202242.

Author information

Authors and Affiliations

  1. Huawei Noah’s Ark Lab, Hong Kong, China

    Lin Ma

  2. School of Information and Electronics, Beijing Institute of Technology, Beijing, China

    Chenwei Deng

  3. School of Computer Engineering, Nanyang Technological University, Singapore, Singapore

    Weisi Lin

  4. Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China

    King Ngi Ngan

  5. National Astronomical Observatories, Chinese Academy of Sciences, Beijing, China

    Long Xu

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  1. Lin Ma
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  2. Chenwei Deng
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  3. Weisi Lin
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  4. King Ngi Ngan
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  5. Long Xu
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Correspondence to Lin Ma .

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Editors and Affiliations

  1. School of Information and Electronics, Beijing Institute of Technology, Beijing, China

    Chenwei Deng

  2. Huawei Noah’s Ark Lab, Quarry Bay, Hong Kong SAR

    Lin Ma

  3. School of Computer Engineering, Nanyang Technological University, Singapore

    Weisi Lin

  4. Department of Electronic Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong SAR

    King Ngi Ngan

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Ma, L., Deng, C., Lin, W., Ngan, K.N., Xu, L. (2015). Retargeted Image Quality Assessment: Current Progresses and Future Trends. In: Deng, C., Ma, L., Lin, W., Ngan, K. (eds) Visual Signal Quality Assessment. Springer, Cham. https://doi.org/10.1007/978-3-319-10368-6_8

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  • DOI: https://doi.org/10.1007/978-3-319-10368-6_8

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  • Online ISBN: 978-3-319-10368-6

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