The modulation of light is important in phase holographic data storage, and different spatial light modulators have different modulation capabilities for light. In this study, a lens less non-interference phase reconstruction system based on deep learning is applied to evaluate the performance differences of different spatial light modulators in holographic data storage. The performance differences are evaluated, which include the deep learning results versus pixel crosstalk results for phased holographic optical storage.
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