Deep-Learning-Based Dynamic Range Compression for 3D Scene Hologram
2021
This study proposes a dynamic-range compression for digital holograms generated from three-dimensional scenes using deep neural network (DNN). This method uses an error diffusion algorithm to binarize holograms with an 8-bit gradation; moreover, the DNN predicts the original gradation holograms from binary holograms. This method’s performance exceeds that of JPEG 2000 and high-efficiency video coding.
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