Biblio
Training a feed-forward network for the fast neural style transfer of images has proven successful, but the naive extension of processing videos frame by frame is prone to producing flickering results. We propose the first end-to-end network for online video style transfer, which generates temporally coherent stylized video sequences in near realtime. Two key ideas include an efficient network by incorporating short-term coherence, and propagating short-term coherence to long-term, which ensures consistency over a longer period of time. Our network can incorporate different image stylization networks and clearly outperforms the per-frame baseline both qualitatively and quantitatively. Moreover, it can achieve visually comparable coherence to optimization-based video style transfer, but is three orders of magnitude faster.
Optical Coherence Tomography (OCT) has shown a great potential as a complementary imaging tool in the diagnosis of skin diseases. Speckle noise is the most prominent artifact present in OCT images and could limit the interpretation and detection capabilities. In this work we evaluate various denoising filters with high edge-preserving potential for the reduction of speckle noise in 256 dermatological OCT B-scans. Our results show that the Enhanced Sigma Filter and the Block Matching 3-D (BM3D) as 2D denoising filters and the Wavelet Multiframe algorithm considering adjacent B-scans achieved the best results in terms of the enhancement quality metrics used. Our results suggest that a combination of 2D filtering followed by a wavelet based compounding algorithm may significantly reduce speckle, increasing signal-to-noise and contrast-to-noise ratios, without the need of extra acquisitions of the same frame.
Compressive sensing (CS) is a novel technology for sparse signal acquisition with sub-Nyquist sampling rate but with relative high resolution. Photonics-assisted CS has attracted much attention recently due the benefit of wide bandwidth provided by photonics. This paper discusses the approaches to realizing photonics-assisted CS.
A technical method regarding to the improvement of transmission capacity of an optical wireless orthogonal frequency division multiplexing (OFDM) link based on a visible light emitting diode (LED) is proposed in this paper. An original OFDM signal, which is encoded by various multilevel digital modulations such as quadrature phase shift keying (QPSK), and quadrature amplitude modulation (QAM), is converted into a sparse one and then compressed using an adaptive sampling with inverse discrete cosine transform, while its error-free reconstruction is implemented using a L1-minimization based on a Bayesian compressive sensing (CS). In case of QPSK symbols, the transmission capacity of the optical wireless OFDM link was increased from 31.12 Mb/s to 51.87 Mb/s at the compression ratio of 40 %, while It was improved from 62.5 Mb/s to 78.13 Mb/s at the compression ratio of 20 % under the 16-QAM symbols in the error free wireless transmission (forward error correction limit: bit error rate of 10-3).
We propose an optical security method for object authentication using photon-counting encryption implemented with phase encoded QR codes. By combining the full phase double-random-phase encryption with photon-counting imaging method and applying an iterative Huffman coding technique, we are able to encrypt and compress an image containing primary information about the object. This data can then be stored inside of an optically phase encoded QR code for robust read out, decryption, and authentication. The optically encoded QR code is verified by examining the speckle signature of the optical masks using statistical analysis. Optical experimental results are presented to demonstrate the performance of the system. In addition, experiments with a commercial Smartphone to read the optically encoded QR code are presented. To the best of our knowledge, this is the first report on integrating photon-counting security with optically phase encoded QR codes.