Combining Defocus and Photoconsistency for Depth Map Estimation in 3D Integral Imaging

  • H. Espinos-Morato
  • P. Latorre-Carmona
  • J. Martinez Sotoca
  • F. Pla
  • B. Javidi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10255)


This paper presents the application of a depth estimation method for scenes acquired using a Synthetic Aperture Integral Imaging (SAII) technique. SAII is an autostereoscopic technique consisting of an array of cameras that acquires images from different perspectives. The depth estimation method combines a defocus and a correspondence measure. This approach obtains consistent results and shows noticeable improvement in the depth estimation as compared to a minimum variance minimisation strategy, also tested in our scenes. Further improvements are obtained for both methods when they are fed into a regularisation approach that takes into account the depth in the spatial neighbourhood of a pixel.


Integral imaging Depth map Regularisation Defocus Minimum variance 



This work was supported by the Spanish Ministry of Economy and Competitiveness (MINECO) under the projects SEOSAT (ESP2013-48458-C4-3-P) and MTM2013-48371-C2-2-P, by the Generalitat Valenciana through the project PROMETEO-II-2014-062, and by the University Jaume I through the project UJI-P11B2014-09. B. Javidi would like to acknowledge support under NSF/IIS-1422179.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • H. Espinos-Morato
    • 1
    • 3
  • P. Latorre-Carmona
    • 1
  • J. Martinez Sotoca
    • 1
  • F. Pla
    • 1
  • B. Javidi
    • 2
  1. 1.Institute of New Imaging Technologies - INITUniversity Jaume I CastellonCastellon de la PlanaSpain
  2. 2.Department of Electrical and Computer EngineeringUniversity of ConnecticutStorrsUSA
  3. 3.Mathematical Modelling and Numeric Simulation GroupCatholic University of ValenciaValenciaSpain

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