No embedding: A novel image cryptosystem for meaningful encryption

In this paper, we propose a novel image cryptosystem, which enables to encrypt the secret images with a smaller-size cover image. Compared with the existing meaningful encryption methods, our cryptosystem has three advantages: (1) non-embedding encryption, i.e., there isn’t any data embedding into the cover image during the encryption process. (2) Our cryptosystem can simultaneously encrypt multiple secret images with one cover image, which greatly improves the security of secret images. (3) Our cryptosystem can accomplish not only the meaningful encryption, but also the meaningless encryption. Thus, people don’t switch encryption methods when meeting different encryption requirements. Our scheme leverages the popular coupled dictionary learning and compressive sensing techniques to accomplish the whole task. Specifically, we use the coupled dictionaries to build connection between the cover image and the secret image, and apply the compressive sensing to decrypt the secret image. To demonstrate the effectiveness of the proposed cryptosystem, a series of experiments are conducted. Experimental results on gray images and colorful RGB images verify its superiority.     

多形态稀疏性正则化的图像超分辨率算法

 如何设计更加高效并能保持图像几何和纹理结构的多幅图像超分辨模型和算法是目前该领域有待解决的难点问题.针对图像的几何、纹理结构形态,分别建立符合类内强稀疏而类间强不相干的几何结构和纹理分量稀疏表示子成份字典,形成图像的多形态稀疏表示模型,进而提出一种新的基于多形态稀疏性正则化的多帧图像超分辨凸变分模型,模型中的正则项刻画了理想图像在多成份字典下的稀疏性先验约束,保真项度量其在退化模型下与观测信号的一致性,采用交替迭代法对该多变量优化问题进行数值求解,每一子问题采用前向后向的算法分裂法进行快速求解.针对可见光与红外图像序列进行了数值仿真,实验结果验证了本文模型与数值算法的有效性.     

电子镇流器智能化在线检测系统研究

电子节能灯在我国已经得到大力推广使用,但目前节能灯镇流器大规模生产流程中大多仍采用传统人工方式进行产品故障检测。设计了以PC机为上位机,单片机为底层处理器、基于LabVIEW及故障字典诊断技术原理构成智能化电子镇流器在线检测系统,详细介绍系统的组成及应用,验证了系统设计的可行性,实用性及灵活性。     

基于LASSO的雷达脉压压缩方法

雷达抗干扰性能是衡量一部雷达优劣的重要指标,直接决定着雷达作战效能的发挥。常见的抗干扰措施有副瓣对消、脉冲压缩、动目标检测、恒虚警处理等。文中结合LASSO回归算法,提出了一种基于LASSO的脉冲压缩抗干扰措施。该方法利用LASSO回归具有稀疏性的特质,结合雷达回波信号设置匹配字典,使用冗余预测变量构造数据集,并使用交叉验证构造LASSO模型,拟合识别预测变量,实现了目标检测。将该方法与脉冲压缩方法对比,仿真实验证明采用LASSO算法不仅不需要考虑旁瓣的影响,还获得了更好的目标分辨能力,并且在较小信噪比条件下目标检测效果也比较好。     

一种改进整词二分法的中文分词词典设计

汉语自动分词是汉语信息处理的前提,词典是汉语自动分词的基础,分词词典机制的优劣直接影响到中文分词的速度和效率.针对常用的分词方法--正向匹配分词法的特征,在已有整词二分词典的基础上加以改进,设计了一种基于Hash索引、二叉树以及动态一维数组结构的中文分词词典,相对于传统的基于Hash索引的分词词典,减小了词典的空间复杂度,提高了汉语分词的速度,最主要的是改进后的词典在增添新词时比以往的词典更为容易.     

A Method on Analog Circuit Fault Diagnosis with Tolerance

In this paper, it is proved that the direction of the node-voltage difference vector, which is the difference between the node-voltage vector at faulty state and the one at the nominal state, is determined only by the location of the faulty clement in linear analog circuits. Considering that the direction of the node-voltage sensitivity vector is the same as the one of the node-voltage difference vector and also considering that the module of the node-voltage sensitivity vector presents the weight of the parameter of faulty element deviation relative to the voltage difference, fault dictionary is set up based on node-voltage sensitivity vectors. A decision algorithm is proposed concerned with both the location and the parameter difference of the faulty element. Single fault and multi-fault can be diagnosed while the circuit parameters deviate within the tolerance range of 10 %.     

Blind single-image super resolution based on compressive sensing

Blind super resolution is an interesting area in image processing that can restore high resolution (HR) image without requiring prior information of the volatile point spread function (PSF). In this paper, a novel framework is proposed for blind single-image super resolution (SISR) problem based on compressive sensing (CS) framework that is one of the first works that considers general PSFs. The fundamental idea in the proposed approach is to use sparsity on a known sparse transform domain as a powerful regularizer in both the image and blur domains. Therefore, a new cost function with respect to the unknown HR image patch and PSF kernel is presented and minimization is performed based on two subproblems that are modeled similar to that of CS. Simulation results demonstrate the effectiveness of the proposed algorithm that is competitive with methods that use multiple LR images to achieve a single HR image.     

基于Trie树的快速电子词典开发

当今社会在步入一个大数据时代,时间和效率举足轻重。因此设计和开发出一款能快速检索目标词汇的电子词典具有十分重要的现实意义。开发的电子词典系统运用Windows API开发,采用Trie树的数据结构设计。结果表明:电子词典实现了Trie树结构的存取和快速Hash映射查词,实现主流电子词典常用功能,包括单词查找、添加生词、我的单词本、课程设置、单词测试和帮助等,可满足大部分用户的需求,具有良好的扩展性。     

联合稀疏表示的双次诱发电位提取算法

诱发电位少次提取对于研究大脑活动规律以及临床诊断等具有重要意义.根据脑电信号的特点,本文提出一种基于联合稀疏表示的双次诱发电位信号估计算法.利用诱发电位信号的准周期性和自发脑电信号的随机性,该算法将脑电信号看作为相似成分和相异成分的叠加.神经系统通过相同刺激产生的诱发电位主要在潜伏期和波幅两方面发生变化,因此该算法利用平均诱发电位进行建模,得到稀疏字典,通过联合稀疏表示算法实现双次诱发电位信号的提取.实验结果表明,该算法和其他算法相比获得了更好的效果.     

一种应用于图像修复的非负字典学习算法

提出了一种基于非负稀疏字典学习的图像修复算法,在非负矩阵分解(NMF)的目标函数中增加稀疏约束项,再通过稀疏编码和字典更新两步迭代学习得到训练样本的非负字典,稀疏编码采用的是非负正交匹配追踪(OMP)算法,字典更新则类似经典的KSVD算法;最终根据字典通过光滑L0范数算法得到待修复图像的稀疏系数,进而实现图像的修复。图像修复实验结果表明,本文算法能够对不同类型缺失的图像做到较好的修复,修复的视觉效果和技术指标都优于当前主流算法。