Autoencoder-based holographic image restoration
This work addresses image restoration for holographic memory and QR codes, but appears incremental as it applies an existing autoencoder method to a specific domain.
The authors tackled the problem of restoring holographic images contaminated by direct light, conjugate light, and speckle noise, using an autoencoder-based method, and demonstrated restoration for holographic memory page data and QR codes.
We propose a holographic image restoration method using an autoencoder, which is an artificial neural network. Because holographic reconstructed images are often contaminated by direct light, conjugate light, and speckle noise, the discrimination of reconstructed images may be difficult. In this paper, we demonstrate the restoration of reconstructed images from holograms that record page data in holographic memory and QR codes by using the proposed method.