Fast Encoding Method for Image Vector Quantization Based on Multiple Appropriate Features to Estimate Euclidean Distance

The encoding process of finding the best-matched codeword (winner) for a certain input vector in image vector quantization (VQ) is computationally very expensive due to a lot of k-dimensional Euclidean distance computations. In order to speed up the VQ encoding process, it is beneficial to firstly estimate how large the Euclidean distance is between the input vector and a candidate codeword by using appropriate low dimensional features of a vector instead of an immediate Euclidean distance computation. If the estimated Euclidean distance is large enough, it implies that the current candidate codeword could not be a winner so that it can be rejected safely and thus avoid actual Euclidean distance computation. Sum (1-D), L₂ norm (1-D) and partial sums (2-D) of a vector are used together as the appropriate features in this paper because they are the first three simplest features. Then, four estimations of Euclidean distance between the input vector and a codeword are connected to each other by the Cauchy–Schwarz inequality to realize codeword rejection. For typical standard images with very different details (Lena, F-16, Pepper and Baboon), the final remaining must-do actual Euclidean distance computations can be eliminated obviously and the total computational cost including all overhead can also be reduced obviously compared to the state-of-the-art EEENNS method meanwhile keeping a full search (FS) equivalent PSNR.     

Quantum Bayesian computation

Quantum Bayesian computation is an emerging field that levers the computational gains available from quantum computers. They promise to provide an exponential speed-up in Bayesian computation. Our article adds to the literature in three ways. First, we describe how quantum von Neumann measurement provides quantum versions of popular machine learning algorithms such as Markov chain Monte Carlo and deep learning that are fundamental to Bayesian learning. Second, we describe quantum data encoding methods needed to implement quantum machine learning including the counterparts to traditional feature extraction and kernel embeddings methods. Third, we show how quantum algorithms naturally calculate Bayesian quantities of interest such as posterior distributions and marginal likelihoods. Our goal then is to show how quantum algorithms solve statistical machine learning problems. On the theoretical side, we provide quantum versions of high dimensional regression, Gaussian processes and stochastic gradient descent. On the empirical side, we apply a quantum FFT algorithm to Chicago house price data. Finally, we conclude with directions for future research.     

Phase-Only Encryption and Single Path Decryption System Using Phase-Encoded Exclusive-OR Rules in Fourier Domain

A phase-only encryption scheme using phase-encoded exclusive-OR (XOR) rules in a Fourier plane and a single path decryption system are presented. To generate phase-only encrypted data, a zero-padded original image, multiplied by a random phase image, is Fourier transformed and its real-valued data is encrypted with key data by using phase-encoded XOR rules. Since the original information is encrypted on the Fourier plane, the proposed encryption is more tolerant to loss of key information by scratching or cutting than previous XOR encryption in a space domain. A decryption is simply performed based on 2-f setup with spatial filter by Fourier transform for multiplication phase-only encrypted data with phase-only key data. Due to single path architecture without a reference wave, the proposed system is resistant to mechanical vibrations and fluctuation. Numerical simulations have confirmed the validity of the proposed encryption scheme and simple decryption architecture.     

矢量光束空间偏振编码的研究

矢量光束独特的空间偏振结构使之应用于空间偏振编码成为可能。提出了一种用一阶矢量光束的偏振分布进行极角空间编码的方法。通过矢量光束生成、光束偏振分布再调制实现了空间编码光束的生成,并采用斯托克斯参数法对空间编码光束进行检测。实验结果证实了一阶矢量光束应用于极角空间偏振编码的可行性,为基于空间偏振编码的激光驾束制导提供了新方法。     

Nonlinear image encryption using a fully phase nonzero-order joint transform correlator in the Gyrator domain

A novel nonlinear image encryption scheme based on a fully phase nonzero-order joint transform correlator architecture (JTC) in the Gyrator domain (GD) is proposed. In this encryption scheme, the two non-overlapping data distributions of the input plane of the JTC are fully encoded in phase and this input plane is transformed using the Gyrator transform (GT); the intensity distribution captured in the GD represents a new definition of the joint Gyrator power distribution (JGPD). The JGPD is modified by two nonlinear operations with the purpose of retrieving the encrypted image, with enhancement of the decrypted signal quality and improvement of the overall security. There are three keys used in the encryption scheme, two random phase masks and the rotation angle of the GT, which are all necessary for a proper decryption. Decryption is highly sensitivity to changes of the rotation angle of the GT as well as to little changes in other parameters or keys. The proposed encryption scheme in the GD still preserves the shift-invariance properties originated in the JTC-based encryption in the Fourier domain. The proposed encryption scheme is more resistant to brute force attacks, chosen-plaintext attacks, known-plaintext attacks, and ciphertext-only attacks, as they have been introduced in the cryptanalysis of the JTC-based encryption system. Numerical results are presented and discussed in order to verify and analyze the feasibility and validity of the novel encryption–decryption scheme.     

液晶空间光调制器在阿达玛变换光谱仪中的应用研究——快速精确的解码方法

研究了液晶空间光调制器(LC-SLM)作为固定不动的编码模板应用于阿达玛变换光谱仪(HTS),提出了快速精确的解码方法,给出了由液晶空间光调制器编码模板所带来的均方根信噪比的改善.     

产生特殊聚焦图形的二元光学元件

通过面积编码将伽博（Gabor)波带片的透过率函数的余弦分布等效为二元分布，研制了能产生各种特殊聚焦图形的二元光学元件。根据透镜聚焦的物理原理制作的二元振幅型波带片可以方便地产生多种聚焦线，给出了相应的实验结果，并讨论了改善聚焦效果的优化条件。     

TOCM彩色摄影技术用于大学物理实验的研究

经过多年的发展，采用全光彩色调制器进行彩色摄影的技术已经相当成熟．作为大专院校的学生，有必要了解这一领域的研究成果．为此，开设了TOCM彩色摄影实验，本文介绍了该实验的原理和实验内容．     

基于ZigBee技术的信息交互系统设计与实现

基于生物电的人-机交互（HCI）技术作为特殊场景下常规人-机交互方法的一种补充,具有非常广阔的应用前景。为了解决基于生物电的HCI系统中多用户通信问题,文章设计并实现了一种基于ZigBee技术的信息交互系统。该系统主要由ZigBee无线通信模块、信息生成/处理模块、串口通信模块三部分组成,用以实现多用户间使用眼电信号（EOG）进行无线信息交互。在实验室环境下,眼电信号有效检出率98.2%,传输距离在无遮挡、无路由的情况下可达到70m。实验结果表明该系统具有识别率高、稳定性好、配置简单、使用方便等优点,具有较强的实际应用价值。     

用联合变换相关器实现灰阶图像绝对差度量光学匹配

将绝对差度量（ＡＤＭ）引入联合变换相关器（ＪＴＣ）,实现了灰阶图像光学匹配的计算机模拟实验,利用循环编码方法,通过联合变换相关器一步绝对差度量,相关后的图像通过取高阈值的分割方法来实现对目标的准确判断,针对高斯噪声干扰情况,分析了阈值选择问题,提高了灰阶目标识别抵抗器材怕畸变干扰的能力。