Optimized sampling for view interpolation in light fields using local dictionaries

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摘要

We present an angular superresolution method for light fields captured with a sparse camera array. Our method uses local dictionaries extracted from a sampling mask for upsampling a sparse light field to a dense light field by applying compressed sensing reconstruction. We derive optimal sampling masks by minimizing the coherence for representative global dictionaries. The desired output perspectives and the number of available cameras can be arbitrarily specified. We show that our method yields qualitative improvements compared to previous techniques.

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论文评审过程:Received 10 February 2017, Revised 12 May 2017, Accepted 21 June 2017, Available online 28 June 2017, Version of Record 19 March 2018.

论文官网地址:https://doi.org/10.1016/j.cviu.2017.06.009