Light Field Compression Using Fourier Disparity Layers

2019 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)(2019)

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摘要
In this paper, we present a compression method for light fields based on the Fourier Disparity Layer representation. This light field representation consists in a set of layers that can be efficiently constructed in the Fourier domain from a sparse set of views, and then used to reconstruct intermediate viewpoints without requiring a disparity map. In the proposed compression scheme, a subset of light field views is encoded first and used to construct a Fourier Disparity Layer model from which a second subset of views is predicted. After encoding and decoding the residual of those predicted views, a larger set of decoded views is available, allowing us to refine the layer model in order to predict the next views with increased accuracy. The procedure is repeated until the complete set of light field views is encoded. Following this principle, we investigate in the paper different scanning orders of the light field views and analyse their respective efficiencies regarding the compression performance.
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关键词
decoded views,light field views,light field compression,compression method,Fourier Disparity Layer representation,light field representation,Fourier domain,disparity map,compression scheme,Fourier Disparity Layer model,predicted views,layer model,intermediate viewpoints
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