164 citations · 262 across the 6 of their papers we have counts for
6 papers
Computational ghost imaging using deep learning
Tomoyoshi Shimobaba, Yutaka Endo, Takashi Nishitsuji +8
Computational ghost imaging (CGI) is a single-pixel imaging technique that exploits the correlation between known random patterns and the measured intensity of light transmitted (o…
Fast, large-scale hologram calculation in wavelet domain
Tomoyoshi Shimobaba, Kyoji Matsushima, Takayuki Takahashi +6
We propose a large-scale hologram calculation using WAvelet ShrinkAge-Based superpositIon (WASABI), a wavelet transform-based algorithm. An image-type hologram calculated using the…
Deep-learning-based data page classification for holographic memory
Tomoyoshi Shimobaba, Naoki Kuwata, Mizuha Homma +9
We propose a deep-learning-based classification of data pages used in holographic memory. We numerically investigated the classification performance of a conventional multi-layer p…
Improvement of the image quality of random phase--free holography using an iterative method
Tomoyoshi Shimobaba, Takashi Kakue, Yutaka Endo +8
Our proposed method of random phase-free holography using virtual convergence light can obtain large reconstructed images exceeding the size of the hologram, without the assistance…
Random phase-free kinoform for large objects
Tomoyoshi Shimobaba, Takashi Kakue, Yutaka Endo +7
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, l…
Optical encryption for large-sized images using random phase-free method
Tomoyoshi Shimobaba, Takashi Kakue, Yutaka Endo +7
We propose an optical encryption framework that can encrypt and decrypt large-sized images beyond the size of the encrypted image using our two methods: random phase-free method an…