AI Article Synopsis
- The paper addresses issues related to angular aliasing artifacts when using plenoptic cameras for digital refocusing, proposing a novel solution that detects and removes aliasing during the refocusing process.
- It emphasizes a shift from traditional frequency domain analysis to a spatial domain analysis, helping to identify where aliasing occurs and separate affected areas from unaffected ones.
- Experimental results show that this new approach outperforms classical techniques like prefiltering and depth-dependent rendering on both synthetic and real light field datasets.
Article Abstract
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.
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| http://dx.doi.org/10.1109/TIP.2017.2668613 | DOI Listing |
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