In this paper a novel, to the best of our knowledge, deep neural network (DNN), VUR-Net, is proposed to realize direct and accurate phase unwrapping. The VUR-Net employs a relatively large number of filters in each layer and adopts alternately two types of residual blocks throughout the network, distinguishing it from the previously reported ones. The proposed method enables the wrapped phase map to be unwrapped precisely without any preprocessing or postprocessing operations, even though the map has been degraded by various adverse factors, such as noise, undersampling, deforming, and so on. We compared the VUR-Net with another two state-of-the-art phase unwrapping DNNs, and the corresponding results manifest that our proposal markedly outperforms its counterparts in both accuracy and robustness. In addition, we also developed two new indices to evaluate the phase unwrapping. These indices are proved to be effective and powerful as good candidates for estimating the quality of phase unwrapping.
The compression of the ciphertext of a cryptosystem is desirable considering the dramatic increase in secure data transfer via Internet. In this paper, we propose a simple and universal scheme to compress and decompress the ciphertext of an optical cryptosystem by the aid of deep learning (DL). For compression, the ciphertext is first resized to a relatively small dimension by bilinear interpolation and thereafter condensed by the JPEG2000 standard. For decompression, a well-trained deep neural network (DNN) can be employed to perfectly recover the original ciphertext, in spite of the severe information loss suffered by the compressed file. In contrast with JPEG2000 and JPEG, our proposal can achieve a far smaller size of the compressed file (SCF) while offering comparable decompression quality. In addition, the SCF can be further reduced by compromising the quality of the recovered plaintext. It is also shown that the compression procedure can provide an additional security level, and this may offer new insight into the compressive encryption in optical cryptosystems. Both simulation and experimental results are presented to demonstrate the proposal.
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