基于非负矩阵分解的彩色图像质量评价方法

针对稀疏表示的图像质量评价模型都基于灰度图像,缺少颜色信息,该文提出一种基于非负矩阵分解(NMF)的全参考彩色图像质量评价方法。首先,从自然彩色图像中随机采样,得到训练样本,利用非负矩阵分解,训练得到特征基矩阵,并经过Schmidt正交化,构建特征提取矩阵;其次,根据视觉显著性模型,利用最大视觉显著性和显著性差值两步骤选取视觉重要区域;最后,利用特征提取矩阵,得到低维的特征向量,并最终得到彩色图像质量评价值。实验结果表明,该文方法在LIVE, CSIQ和TID2008 3个图像质量评价库上有很好的表现。3个图像库的平均结果显示,该文方法的综合表现优于所有对比方法。这表明该文方法与主观感知有更好的关联度。     

基于Visual C++的传感器稳定性测试系统设计与实现

本文基于传感器稳定性测试中存在的一些效率低等问题,开发并设计出一套Visual C++的系统.在计算机的主控器上指令编程IO数字量输出卡,完成对G5V-2继电器开关的控制切换.该系统具有网络通讯集成功能,通过TCP/IP协议,能在局域网内实时监视传感器稳定性测试,并且还能远程控制压力控制器以及调温箱,通过模拟工业现场特定环境中的压力以及温度条件等测试传感器的稳定性.     

Sample selection for visual domain adaptation via sparse coding

Visual domain adaptation has attracted much attention and has made great achievement in recent years. It deals with the problem of distribution divergence between source and target domains. Current methods mostly focus on transforming images from different domains into a common space to minimize the distribution divergence. However, there are many irrelevant source samples for target domain even after the transformation. In order to eliminate the irrelevant samples, we develop a sample selection algorithm using sparse coding theory. We do the sample selection in a common subspace of source and target data to find as many as relevant source samples. In the common subspace, data characteristics are preserved by using graph regularization. Therefore, we can select the most relevant samples for our target image classification task. Moreover, in order to build a discriminative classifier for the target domain, we use not only the common part of source and target domains learned in the common subspace but also the specific part of target domain. The algorithm can be extended to handle samples from multiple source domains. Experimental results show that our visual domain adaptation method on the image classification tasks can be very effective for the state-of-the-art datasets.     

Small-world brain functional network altered by watching 2D/3DTV

With the development of display technology, the healthy problems caused by watching 2D/3DTV have received more and more attention. This paper utilized resting-state functional magnetic resonance imaging to study the changes of small-world brain network before and after one-hour 2D/3DTV watching, and explored the brain fatigue mechanism caused by watching 2D/3DTV. We conclude that one-hour watching of 2DTV will not increase the burden of brain. On the contrary, one-hour watching of 3DTV requires the brain to regulate the efficiency of brain areas, such as temporal lobe and occipital lobe, which may explain the fact that watching 3DTV can easier cause brain fatigue than watching 2DTV.     

视讯业务发展思路探讨

视讯业务是集语音、图像、数据于一体的多媒体通信业务,几年来已在电视会议、远程教学等方面得到了快速的发展,多媒体通信将是未来通信发展的必然趋势。随着当前电信业开放所带来的激烈竞争,能否把握视讯业务的运营将成为电信运营商未来市场竞争成败的关键。本文就当前电信业的视讯业务发展现状,论述中国电信视讯业务发展的方向及思路。     

基于“三网融合”的可视化资源协同

网络的宽带化发展有效促进了可视化资源的使用,特别是"三网融合",推动了应用协作和资源共享的发展,在三网间共享资源,实现整个社会信息资源的重复利用和深度挖掘,必将给社会带来巨大的经济效益和社会效益.因此,探索在"三网"间进行可视化资源协同、信息共享是社会信息化发展的重要内容.     

LED电视在2D模式下的视觉健康舒适度测试研究

通过客观量测人眼观视时的各项视觉生理指标,并将各项指标嵌入人眼健康舒适度评价模型进行分析运算。经由583人次的人因实验,从视觉健康舒适度、电视屏幕人眼色觉客观量化反馈以及操控可用性3个方面对12款主流品牌的LED电视样机的视觉健康舒适度与人机交互设计进行了测试与评价。     

用Visual Basic开发个性化图形界面的技术及其实现

Visual Bhsic(VB)是开发Windows环境下图形化应用程序的良好工具，其易学易用已为广大编程爱好者公认。可是VB开发的图形界面中规中矩，已不能满足日益张显个性的要求，就此本文以时钟程序为例，介绍如何用VB开发具有通明效果的不规则图形界面应用程序的关键技术。     

An experimental study on the universality of visual vocabularies

Bag-of-visual-words has been shown to be a powerful image representation and attained success in many computer vision and pattern recognition applications. Usually for a given classification task, researchers choose to build a specific visual vocabulary, and the problem of building a universal visual vocabulary is rarely addressed. In this paper we conduct extensive classification experiments with three features on four image datasets and show that the visual vocabularies built from different datasets can be exchanged without apparent performance loss. Furthermore, we investigate the correlation between the visual vocabularies built from different datasets and find that they are nearly identical, which explains why they are universal across classification tasks. We believe that this work reveals what is behind the universality of visual vocabularies and narrows the gap between bag-of-visual-words and bag-of-words in text domain.     

基于四阶偏微分方程的图像去噪方法实现

针对VB数值计算能力和图像处理能力不足,以及不利于系统开发的缺点,介绍基于VB和MatrixVB并利用四阶偏微分方程实现图像去噪的方法。利用VB作为主要编程语言,借助MatrixVB矩阵运算函数库建立了处理系统,实现了图像去噪功能。该方法将Matlab的强大计算功能与VB的Windows用户界面开发方面的优势结合起来,缩短了软件的开发周期。软件测试结果表明．计算方法正确,方法稳定可靠,算法设计优化,所开发的应用软件具有界面友好,计算速度快,系统资源消耗少,操作简便易行,能满足图像滤波的要求。