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)

Abstract

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.

Keywords

Integral imaging Depth map Regularisation Defocus Minimum variance 

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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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