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3-D Shape Recovery from Image Focus Using Rank Transform

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Book cover Advances in Visual Computing (ISVC 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10073))

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Abstract

Obtaining an accurate and precise depth map is an ultimate goal of 3-D shape recovery. This article proposes a new robust algorithm Rank Transform (RT) for recovering 3-D shape of an object. The rank transform (RT) encodes for each pixel the position of its grey value in the ranking of all the grey values in its neighborhood. Due to its low computational complexity and robustness against noise, it is superior alternative to most of other SFF approaches. The proposed method is experimented using real and synthetic image sequences. The evaluation is gauged on the basis of unimodality and monotonicity of the focus curve. Finally by means of two global statistical metrics Root mean square error (RMSE) and correlation, we show that our method produces – in spite of simplicity- results of competitive quality.

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Author information

Authors and Affiliations

  1. College of E and ME, National University of Sciences and Technology, Islamabad, Pakistan

    Fahad Mahmood, Jawad Mahmood, Waqar Shahid Qureshi & Umar Shahbaz Khan

Authors
  1. Fahad Mahmood
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  2. Jawad Mahmood
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  3. Waqar Shahid Qureshi
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  4. Umar Shahbaz Khan
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Corresponding author

Correspondence to Fahad Mahmood .

Editor information

Editors and Affiliations

  1. University of Nevada, Reno, Nevada, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, California, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, Nevada, USA

    Darko Koracin

  5. The Australian National University, O’Malley, Aust Capital Terr, Australia

    Fatih Porikli

  6. Pilot AI Labs, Redwood City, California, USA

    Sandra Skaff

  7. University of Florida, Gainesville, Florida, USA

    Alireza Entezari

  8. Google Inc., Mountain View, California, USA

    Jianyuan Min

  9. Osaka University, Osaka, Japan

    Daisuke Iwai

  10. The MOVES Institute, Monterey, California, USA

    Amela Sadagic

  11. University of Arizona, Tucson, Arizona, USA

    Carlos Scheidegger

  12. Université Paris-Sud, Orsay, France

    Tobias Isenberg

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© 2016 Springer International Publishing AG

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Mahmood, F., Mahmood, J., Qureshi, W.S., Khan, U.S. (2016). 3-D Shape Recovery from Image Focus Using Rank Transform. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2016. Lecture Notes in Computer Science(), vol 10073. Springer, Cham. https://doi.org/10.1007/978-3-319-50832-0_50

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  • DOI: https://doi.org/10.1007/978-3-319-50832-0_50

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-50831-3

  • Online ISBN: 978-3-319-50832-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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