Takashi Nishitsuji

TL;DR: A deep neural network is used to automatically learn the features of noise-contaminated CGI images and is able to predict low-noise images from new noise- Contamination CGI images.

TL;DR: A new C++ class library for diffraction and CGH calculations, referred to as a CWO++ library, running on a CPU and GPU, which provides diffraction calculations useful for Computer Generated Holograms, digital holography, diffractive optical elements, microscopy, image encryption and decryption and three-dimensional analysis for optical devices.

TL;DR: It is shown that a special-purpose holography computing board, which uses eight large-scale field-programmable gate arrays, can be used to generate 108-pixel holograms that can be updated at a video frame rate, thus allowing 3D movies to be projected.

TL;DR: This work reviews fast calculation techniques for CGH calculation of a point-light-source-based model, which is a simple and general model of a three-dimensional object in an electroholography system.

TL;DR: This study proposes a fast CGH generating algorithm using the circular symmetry of zone plates and computer graphics techniques, and evaluated the proposed method by numerical simulation.