Aliasing Detection and Reduction Scheme on Angularly Undersampled Light Fields

Zhaolin Xiao

doi:10.1109/TIP.2017.2668613

Aliasing Detection and Reduction Scheme on Angularly Undersampled Light Fields

2017-05-01

9

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AI

DOI：10.1109/TIP.2017.2668613

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When using plenoptic camera for digital refocusing, angular undersampling can cause severe (angular) aliasing artifacts. Previous approaches have focused on avoiding aliasing by pre-processing the acquired light field via prefiltering, demosaicing, reparameterization, and so on. In this paper, we present a different solution that first detects and then removes angular aliasing at the light field refocusing stage. Different from previous frequency domain aliasing analysis, we carry out a spatial domain analysis to reveal whether the angular aliasing would occur and uncover where in the image it would occur. The spatial analysis also facilitates easy separation of the aliasing versus non-aliasing regions and angular aliasing removal. Experiments on both synthetic scene and real light field data sets (camera array and Lytro camera) demonstrate that our approach has a number of advantages over the classical prefiltering and depth-dependent light field rendering techniques.

Keyword:

Light field

angular undersampling

aliasing detection

aliasing model

plenoptic imaging

Aliasing Detection and Reduction Scheme on Angularly Undersampled Light Fields

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