Depth estimation for hand-held light field cameras under low light conditions

Depth estimation is one of the new functions provided by hand-held light field cameras. However, the quality of depth estimation is very sensitive to noise, which is especially a problem for scenes under low light conditions. In this paper, we propose a depth estimation flow for light field data, wh...

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Main Authors: Min-Hung Chen, Ching-Fan Chiang, Yi-Chang Lu
Format: Conference Proceeding
Language:English
Subjects:
Arrays
Cameras
Correlation
denoising
Depth estimation
Estimation
Iterative methods
light field
Noise
Noise reduction
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Ching-Fan Chiang
Yi-Chang Lu
description Depth estimation is one of the new functions provided by hand-held light field cameras. However, the quality of depth estimation is very sensitive to noise, which is especially a problem for scenes under low light conditions. In this paper, we propose a depth estimation flow for light field data, which can be fully-automated and no noise characteristics are required a priori. The results of Root Mean Square Error (RMSE) and Percentage of Bad Matching Pixels (PBM) show the effectiveness of this iterative correlation-based depth estimation flow even with basic filtering functions.
doi_str_mv 10.1109/IC3D.2014.7032578
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source IEEE Electronic Library (IEL) Conference Proceedings
subjects Arrays
Cameras
Correlation
denoising
Depth estimation
Estimation
Iterative methods
light field
Noise
Noise reduction
title Depth estimation for hand-held light field cameras under low light conditions
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