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

Author

Min-Hung Chen ; Ching-Fan Chiang ; Yi-Chang Lu

Author_Institution

Grad. Inst. of Electron. Eng., Nat. Taiwan Univ., Taipei, Taiwan

fYear

2014

fDate

9-10 Dec. 2014

Firstpage

1

Lastpage

4

Abstract

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.

Keywords

cameras; filtering theory; image denoising; iterative methods; least mean squares methods; PBM; RMSE; denoising processes; filtering functions; hand-held light field cameras; iterative correlation-based depth estimation flow; low light conditions; noise-resilient depth estimation flow; percentage of bad matching pixels; root mean square error; Arrays; Cameras; Correlation; Estimation; Iterative methods; Noise; Noise reduction; Depth estimation; denoising; light field;

fLanguage

English

Publisher

ieee

Conference_Titel

3D Imaging (IC3D), 2014 International Conference on

Conference_Location

Liege

Type

conf

DOI

10.1109/IC3D.2014.7032578

Filename

7032578