Depth and All-in-Focus Image Estimation in Synthetic Aperture Integral Imaging Under Partial Occlusions

A common assumption in the integral imaging reconstruction is that a pixel will be photo-consistent if all viewpoints observed by the different cameras converge at a single point when focusing at the proper depth. However, the presence of occlusions between objects in the scene prevents this from be...

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Main Authors: Jose Martinez Sotoca, Pedro Latorre-Carmona, Filiberto Pla, Bahram Javidi
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8572694/
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spelling doaj-2177a05e9f0040269c2f1933748dac452021-03-29T22:06:16ZengIEEEIEEE Access2169-35362019-01-0171052106710.1109/ACCESS.2018.28862358572694Depth and All-in-Focus Image Estimation in Synthetic Aperture Integral Imaging Under Partial OcclusionsJose Martinez Sotoca0Pedro Latorre-Carmona1https://orcid.org/0000-0001-6984-5173Filiberto Pla2Bahram Javidi3Institute of New Imaging Technologies, Universitat Jaume I, Castellon de la Plana, SpainInstitute of New Imaging Technologies, Universitat Jaume I, Castellon de la Plana, SpainInstitute of New Imaging Technologies, Universitat Jaume I, Castellon de la Plana, SpainDepartment of Electrical and Computer Engineering, University of Connecticut, Storrs, CT, USAA common assumption in the integral imaging reconstruction is that a pixel will be photo-consistent if all viewpoints observed by the different cameras converge at a single point when focusing at the proper depth. However, the presence of occlusions between objects in the scene prevents this from being fulfilled. In this paper, a novel depth and all-in focus image estimation method is presented, based on a photo-consistency measure that uses the median criterion in relation to the elemental images. The interest of this approach is to find a solution to detect which camera correctly sees the partially occluded object at a certain depth and allows for a precise solution to the object depth. In addition, a robust solution is proposed to detect the boundary limits between partially occluded objects, which are subsequently used during the regularization depth estimation process. The experimental results show that the proposed method outperforms other state-of-the-art depth estimation methods in a synthetic aperture integral imaging framework.https://ieeexplore.ieee.org/document/8572694/Synthetic aperture integral imagingdepth map estimationall-in-focus imagepartial occlusions3D image processing
collection DOAJ
language English
format Article
sources DOAJ
author Jose Martinez Sotoca
Pedro Latorre-Carmona
Filiberto Pla
Bahram Javidi
spellingShingle Jose Martinez Sotoca
Pedro Latorre-Carmona
Filiberto Pla
Bahram Javidi
Depth and All-in-Focus Image Estimation in Synthetic Aperture Integral Imaging Under Partial Occlusions
IEEE Access
Synthetic aperture integral imaging
depth map estimation
all-in-focus image
partial occlusions
3D image processing
author_facet Jose Martinez Sotoca
Pedro Latorre-Carmona
Filiberto Pla
Bahram Javidi
author_sort Jose Martinez Sotoca
title Depth and All-in-Focus Image Estimation in Synthetic Aperture Integral Imaging Under Partial Occlusions
title_short Depth and All-in-Focus Image Estimation in Synthetic Aperture Integral Imaging Under Partial Occlusions
title_full Depth and All-in-Focus Image Estimation in Synthetic Aperture Integral Imaging Under Partial Occlusions
title_fullStr Depth and All-in-Focus Image Estimation in Synthetic Aperture Integral Imaging Under Partial Occlusions
title_full_unstemmed Depth and All-in-Focus Image Estimation in Synthetic Aperture Integral Imaging Under Partial Occlusions
title_sort depth and all-in-focus image estimation in synthetic aperture integral imaging under partial occlusions
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2019-01-01
description A common assumption in the integral imaging reconstruction is that a pixel will be photo-consistent if all viewpoints observed by the different cameras converge at a single point when focusing at the proper depth. However, the presence of occlusions between objects in the scene prevents this from being fulfilled. In this paper, a novel depth and all-in focus image estimation method is presented, based on a photo-consistency measure that uses the median criterion in relation to the elemental images. The interest of this approach is to find a solution to detect which camera correctly sees the partially occluded object at a certain depth and allows for a precise solution to the object depth. In addition, a robust solution is proposed to detect the boundary limits between partially occluded objects, which are subsequently used during the regularization depth estimation process. The experimental results show that the proposed method outperforms other state-of-the-art depth estimation methods in a synthetic aperture integral imaging framework.
topic Synthetic aperture integral imaging
depth map estimation
all-in-focus image
partial occlusions
3D image processing
url https://ieeexplore.ieee.org/document/8572694/
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AT filibertopla depthandallinfocusimageestimationinsyntheticapertureintegralimagingunderpartialocclusions
AT bahramjavidi depthandallinfocusimageestimationinsyntheticapertureintegralimagingunderpartialocclusions
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