{"id":{"repo_id":"umkc","oai_identifier":"oai:mospace.umsystem.edu:10355/60658"},"canonical_url":"https://search.dev.ndltd.org/etd/umkc/oai:mospace.umsystem.edu:10355/60658","repository":{"repo_id":"umkc","name":"University of Missouri - Kansas City","base_url":"https://mospace.umsystem.edu/oai/request"},"display":{"title":"Advanced Light Field Frame Prediction For Optimized Compression","abstract":"Current light field compression techniques lack robustness to handle both rate distortion optimized motion compensation as well as latency during the encoding and decoding process. This paper focuses on a contribution approach that uses advanced prediction with affine and translational motion models and optimized view prediction structures. This method allows a significant compression performance gain over the current state of art of hierarchical temporal coding by 13.9%. The proposed method introduces an optimized encoding order that takes advantage of each group of pictures structure in order to leverage the dense perspective model of light field imagery. Both a global perspective model and a local affine model can be combined to show substantial distortion reduction at low processor costs. This contribution approach leads to an efficient and robust compression scheme for light field datasets.","abstract_html":"Current light field compression techniques lack robustness to handle both rate distortion optimized motion compensation as well as latency during the encoding and decoding process. This paper focuses on a contribution approach that uses advanced prediction with affine and translational motion models and optimized view prediction structures. This method allows a significant compression performance gain over the current state of art of hierarchical temporal coding by 13.9%. The proposed method introduces an optimized encoding order that takes advantage of each group of pictures structure in order to leverage the dense perspective model of light field imagery. Both a global perspective model and a local affine model can be combined to show substantial distortion reduction at low processor costs. 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