Depth Map Estimation Using Census Transform for Light Field Cameras

Takayuki TOMIOKA  Kazu MISHIBA  Yuji OYAMADA  Katsuya KONDO  

IEICE TRANSACTIONS on Information and Systems   Vol.E100-D   No.11   pp.2711-2720
Publication Date: 2017/11/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2017EDP7052
Type of Manuscript: PAPER
Category: Image Recognition, Computer Vision
light field camera,  Lytro,  depth map,  census transform,  

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Depth estimation for a lense-array type light field camera is a challenging problem because of the sensor noise and the radiometric distortion which is a global brightness change among sub-aperture images caused by a vignetting effect of the micro-lenses. We propose a depth map estimation method which has robustness against sensor noise and radiometric distortion. Our method first binarizes sub-aperture images by applying the census transform. Next, the binarized images are matched by computing the majority operations between corresponding bits and summing up the Hamming distance. An initial depth obtained by matching has ambiguity caused by extremely short baselines among sub-aperture images. After an initial depth estimation process, we refine the result with following refinement steps. Our refinement steps first approximate the initial depth as a set of depth planes. Next, we optimize the result of plane fitting with an edge-preserving smoothness term. Experiments show that our method outperforms the conventional methods.