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- W2897548814 abstract "In this paper, we propose a novel light field image compression scheme by exploiting the intrinsic similarity of light field images with deep learning. In particular, instead of conveying all LF sub-views, only sparsely sampled LF sub-views are compressed and the remaining sub-views are reconstructed from the coded sub-views in the neighbourhood with convolutional neural network (CNN). To jointly suppress the artifacts induced in compression and reconstruct the un-coded views with high geometric accuracy, a multi-view joint enhancement network is introduced to improve the coding performance. Extensive experiments show the superior compression performance of our scheme compared with the state-of-the-art methods." @default.
- W2897548814 created "2018-10-26" @default.
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- W2897548814 date "2018-07-01" @default.
- W2897548814 modified "2023-10-16" @default.
- W2897548814 title "Light Field Image Compression Based on Deep Learning" @default.
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- W2897548814 doi "https://doi.org/10.1109/icme.2018.8486546" @default.
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