Convolutional neural network-based data page classification for holographic memory.

We propose a deep-learning-based classification of data pages used in holographic memory. We numerically investigated the classification performance of a conventional multilayer perceptron (MLP) and a deep neural network, under the condition that reconstructed page data are contaminated by some noise and are randomly laterally shifted. When data pages are randomly laterally shifted, the MLP was found to have a classification accuracy of 93.

Holographic microinformation hiding.

We propose a holographic microinformation hiding scheme in which the embedding information to be embedded is small and imperceptible to the human eyes. This scheme converts the embedding information into a complex amplitude via scaled diffraction. The complex amplitude of the reduced embedding information is added to the complex amplitude of the host image, followed by conversion to a hologram.

Color computer-generated hologram generation using the random phase-free method and color space conversion.

We propose two calculation methods of generating color computer-generated holograms (CGHs) with the random phase-free method and color space conversion in order to improve the image quality and accelerate the calculation. The random phase-free method improves the image quality in monochrome CGH, but it is not performed in color CGH. We first aimed to improve the image quality of color CGH using the random phase-free method and then to accelerate the color CGH generation with a combination of the random phase-free method and color space conversion method, which accelerates the color CGH calculation due to down-sampling of the color components converted by color space conversion.

Random phase-free kinoform for large objects.

We propose a random phase-free kinoform for large objects. When not using the random phase in kinoform calculation, the reconstructed images from the kinoform are heavy degraded, like edge-only preserved images. In addition, the kinoform cannot record an entire object that exceeds the kinoform size because the object light does not widely spread.