Robust and Dense Depth Estimation for Light Field Images

We propose a depth estimation method for light field images. Light field images can be considered as a collection of 2D images taken from different viewpoints arranged in a regular grid. We exploit this configuration and compute the disparity maps between specific pairs of views. This computation is...

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Bibliographic Details
Published in:IEEE transactions on image processing 2017-04, Vol.26 (4), p.1873-1886
Main Authors: Navarro, Julia, Buades, Antoni
Format: Article
Language:English
Subjects:
Algorithm design and analysis
Cameras
disparity estimation
Estimation
Interpolation
Lenses
Light field image
Robustness
State of the art
stereo interpolation
stereo problem
Two dimensional displays
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Summary:We propose a depth estimation method for light field images. Light field images can be considered as a collection of 2D images taken from different viewpoints arranged in a regular grid. We exploit this configuration and compute the disparity maps between specific pairs of views. This computation is carried out by a state-of-the-art two-view stereo method providing a nondense disparity estimation. We propose a disparity interpolation method increasing the density and improving the accuracy of this initial estimate. Disparities obtained from several pairs of views are fused to obtain a unique and robust estimation. Finally, different experiments on synthetic and real images show how the proposed method outperforms the state-of-the-art results.
ISSN:1057-7149
1941-0042
DOI:10.1109/TIP.2017.2666041