基于引导滤波和多尺度局部自相似单幅红外图像超分辨率方法

本文针对红外图像存在分辨率不高、对比度低的特点,提出了基于引导滤波和多尺度局部自相似性红外单幅图像超分辨率算法。首先,该方法引进了类高斯分布的“类高斯核”,在此基础上构建均值引导滤波器,该滤波器是一种线性边缘保持滤波器,可以得到图像的高频细节。其次,根据图像的自相似性,对初始高分辨率图像和原始低分辨率图像进行分块,得到待匹配窗和搜索窗,根据非局部均值（NLM）,待匹配窗图像块的值利用搜索窗中相似块的加权平均计算得到。再次,利用图像自相似性,待匹配窗在搜索窗的邻域内进行匹配搜索,找到与待匹配窗最相似的匹配块,计算出最佳匹配块的高频细节图像块,与相似块的加权平均值相加,重构出高分辨率待匹配窗。最后,合并所有的超分辨率重构的待匹配窗,相邻图像块重叠区域的像素值使用平均融合得到,得到最终的超分辨率图像。实验结果表明,本文算法不仅能很好重构图像的高频细节,还能很好的恢复图像的纹理特征,得到的结果不仅边缘更清晰更真实,而且纹理更加丰富。     

改进相似性度量模型的单幅图像自学习超分辨算法

在自学习超分辨算法中,高低分辨率图像块匹配是否准确是算法的关键。在高低分辨率图像块匹配过程中,考虑图像块纹理结构的重要性,提出了一种基于纹理约束的图像块相似性度量模型,应用该模型完成了高低分辨率图像块更为准确的匹配,使超分辨结果图像的细节更加丰富,进一步提高了图像质量。该算法仅使用了单幅低分辨率图像自身的相关先验信息,有效提升了图像的空间分辨率。实验结果表明,与双三次插值算法、自相似学习超分辨算法相比,本文提出的算法超分辨视觉效果更好,并且在客观评价指标中同样表现良好。     

相似性约束的视频超分辨率重建

图像的相似性对超分辨率重建具有重要作用,但是单幅图像不能提供足够的相似信息.提出一种基于相似性约束的视频超分辨率重建算法,针对需要重建的视频帧,通过光流场的初始运动估计和精细的块匹配,搜索到视频序列中具有相似的信息;然后利用相似信息不断修正迭代反投影中的重建误差.实验结果表明本文算法能够增加图像细节,并且可以消除边缘出现的人造效应,获得清晰的图像边缘.     

基于局部回归模型的图像超分辨率重建

针对基于稀疏重建的图像超分辨率(SR)算法一般需要外部训练样本,重建质量取决于待重建图像与训练样本的相似度的问题,提出一种基于局部回归模型的图像超分辨率重建算法。利用局部图像结构会在不同的图像尺度对应位置重复出现的事实,建立从低到高分辨率图像块的非线性映射函数一阶近似模型用于超分辨率重建。其中,非线性映射函数的先验模型是直接对输入图像及其低频带图像的对应位样本块对通过字典学习的方法得到。重建图像块时利用图像中的非局部自相似性,对多个非局部自相似块分别应用一阶回归模型,加权综合得到高分辨率图像块。实验结果表明,该算法重建的图像与同样利用图像具有自相似性的相关超分辨率算法相比,峰值信噪比(PSNR)平均提高0.3~1.1 dB,主观重建效果亦有明显提高。     

正则化技术和低秩矩阵在稀疏表示超分辨率算法中的应用

为了有效地利用图像的特征作为指导重建的先验知识,解决常规超分辨率算法对边缘与结构等细节恢复不足的问题,提出一种改进的超分辨率算法.对待重建图像进行低秩分解,得到不同特征的低秩子图像和稀疏子图像;对于低秩子图像,提出采用基于正则化技术的稀疏表示超分辨率算法进行重建,先通过在低秩子图像中寻找相似图像块构造非局部相似正则化项,得到图像的非局部冗余,以保持边缘信息;再通过局部线性嵌入方法构造流形学习正则化项,获得图像的结构先验知识,以增强结构信息.对于稀疏子图像则不参与稀疏表示超分辨率重建,而是采用双三次插值法进行重建.实验结果表明,与其他算法相比,无论在主观视觉效果上,还是在峰值信噪比和结构相似性指标上,文中算法都有显著的提高.     

基于字典学习与结构自相似性的码本映射超分辨率算法

图像的空间分辨率受成像环境、硬件制造水平和成本等多方面因素的影响,存在一定的局限性.为了提高图像的空间分辨率,提出一种基于字典学习与结构自相似性的码本映射超分辨率算法.首先利用训练集构建与图像高低频分量对应的高低频码本,将高低频码本作为训练样本获取高低频字典;然后在初始重建图像中搜索目标图像块的相似图像块,利用相似图像块构建非局部约束项;最后通过求解含有非局部约束项的l0范数最小化问题获取目标图像块的稀疏表示系数,并利用高低频字典重建高分辨率图像块.该算法利用高低频字典表示目标图像块,而不是直接采用高低频码本,提高了算法的运算效率;利用相似图像块构建正则化约束项,提高了重建图像的质量.实验结果表明,与LLE,Sc SR和NARM等算法相比,文中算法取得的超分辨率重建效果更好.     

基于字典学习和非局部相似的超分辨率重建

为提高单帧降质图像的分辨率,提出了一种基于字典学习和非局部相似性的超分辨率重建算法。该算法主要将高分辨率图像减去利用迭代反投影重建结果得到差值图像,再利用K-奇异值分解(K-SVD)算法和联合字典生成的思想形成的字典训练方法,训练差值图像块和低分辨率图像块得到对应的高、低分辨率字典用于超分辨重建。此外,引入非局部相似性的正则项约束以提高重建图像的质量。实验结果表明,所提算法重建得到的图像在主观视觉效果和客观评价上优于基于例子学习的超分辨率算法。     

基于自相似性车载采集城市街景图像的重建

大众化的车载为确保实时、高速的图像显示及图像存储,其捕获的图像通常会呈现出较低的分辨率,严重影响了突发状况时有效图像信息的获取。针对该低分辨率的城市街景图像采用了一种基于透视变换、高频补偿的自相似性图像重建方法。该算法在仿射变换的基础上增加了透视变换来进行图像块的匹配,并对每一个匹配的图像块进行高频补偿以恢复构建图像金字塔时丢失的高频信息,通过多尺度非局部方法搜索图像金字塔,合成匹配图像块得到最终的高分辨率图像。采用该算法对采集到的大量低分辨率城市街景图像进行重建,并与ScSR、Upscaling、SCN这三种典型的算法进行对比,实验结果表明该算法在几种盲评价指标上较其他算法好,在提高图像分辨率的同时能保持图像的边缘和细节信息。     

基于多尺度结构自相似性的单幅图像超分辨率算法

多尺度结构自相似性是指同一幅图像中存在相同尺度或不同尺度的相似结构,这种多尺度图像结构自相似性广泛存在于遥感图像中.本文提出了一种基于多尺度结构自相似性的单幅图像超分辨率（Super resolution,SR）算法,该算法结合了压缩感知框架与图像结构自相似性,利用非局部方法和基于图像金字塔的K-SVD字典学习方法,将蕴含在相同尺度和不同尺度相似图像块中的附加信息在压缩感知的框架下加入到重构图像中.本文算法的优势在于,它仅借助于单幅低分辨率图像自身所蕴含的信息,实现了空间分辨率的提升.实验表明,与CSSS算法和ASDSAR算法相比,本文算法更有效地提升了遥感图像的空间分辨率.     

基于超像素分割的非局部均值去噪方法

针对非局部均值(NLM)去噪算法在变化丰富的纹理区域采用平移窗口的方法选择相似块的不足进行了研究,提出一种基于超像素分割的非局部均值去噪算法。该方法充分考虑非局部均值去噪算法中相似性对噪声去除的影响,利用经过超像素分割处理得到的图像块内部相邻像素间以及纹理边缘都具有一定相似性的特点,在超像素分割块基础上优化纹理区域相似窗口的选择策略,提高图像块与中心像素块之间的相似性,从而达到提升非局部均值算法的去噪水平、边缘纹理不被模糊的目的。在多幅经典自然图像上的实验结果表明,该方法能够有效的去除图像中包含的噪声信息,相比于传统的非局部均值方法,保留了更多的纹理信息。     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

煤矿井下安全监控分站的设计及其仿真实现

为了设计一种具有低成本、低功耗、易操作、功能强且可靠性高的煤矿井下安全分站,针对煤矿安全生产实际,文章提出了采用MCS-51系列单片机为核心、具有CAN总线通信接口的煤矿井下安全监控分站的设计方案;首先给出煤矿井下安全监控分站的整体构架设计,然后着重阐述模拟量输入信号处理系统的设计过程,最后说明单片机最小系统及其键盘、显示、报警、通信等各个组成部分的设计;为验证设计方案的可行性与有效性,使用Proteus软件对设计内容进行仿真验证,设计的煤矿井下安全监控分站具有瓦斯、温度等模拟量参数超标报警功能和电机开停、风门开闭等开关量指示功能;仿真结果表明:设计的煤矿井下安全监控分站具有一定的实际应用价值.     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

View-based model-driven architecture for enhancing maintainability of data access services

In modern service-oriented architectures, database access is done by a special type of services, the so-called data access services (DAS). Though, particularly in data-intensive applications, using and developing DAS are very common today, the link between the DAS and their implementation, e.g. a layer of data access objects (DAOs) encapsulating the database queries, still is not sufficiently elaborated, yet. As a result, as the number of DAS grows, finding the desired DAS for reuse and/or associated documentation can become an impossible task. In this paper we focus on bridging this gap between the DAS and their implementation by presenting a view-based, model-driven data access architecture (VMDA) managing models of the DAS, DAOs and database queries in a queryable manner. Our models support tailored views of different stakeholders and are scalable with all types of DAS implementations. In this paper we show that our view-based and model driven architecture approach can enhance software development productivity and maintainability by improving DAS documentation. Moreover, our VMDA opens a wide range of applications such as evaluating DAS usage for DAS performance optimization. Furthermore, we provide tool support and illustrate the applicability of our VMDA in a large-scale case study. Finally, we quantitatively prove that our approach performs with acceptable response times.     

A pragmatic multi-method investigation of discrepant technological events: Coping,attributions, and ‘accidental’ learning

Discrepant technological events or situations that entail a problem, a misunderstanding or a difficulty with the Information Technology (IT) being employed, are common in the workplace, and can lead to frustration and avoidance behaviors. Little is known, however, about how individuals cope with these events. This paper examines these events by using a multi-method pragmatic approach informed by coping theory. The results of two studies – a critical incident study and an experiment – serve to build and test, respectively, a theoretical model that posits that individuals use a variety of strategies when dealing with these events: they experience negative emotions, make external attributions, and adopt engagement coping strategies directed at solving the event, eventually switching to a disengagement coping strategy when they feel they have no control over the situation. Furthermore, users’ efforts may result in ‘accidental’ learning as they try to overcome the discrepant IT events through engagement coping. The paper ends with a discussion of the results in light of existing literature, future opportunities for research, and implications for practice.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

The Distributed Time-Triggered Simulation Scheme: Core Principles and Supporting Execution Engine

Distributed real-time simulation is a young technology field but its practice is under increasing demands. In recent years the author and his collaborators have been establishing a new approach called the distributed time-triggered simulation (DTS) scheme which is conceptually simple and easy to use but widely applicable. The concept was initiated in the course of developing a new-generation object-oriented real-time programming scheme called the time-triggered message-triggered object (TMO) programming scheme. Some fundamental issues inherent in distributed real-time simulation that were learned during recent experimental studies are discussed along with some approaches for resolving the issues. An execution engine developed to support both the TMOs engaged in control computation and the TMOs engaged in DTS is also discussed along with its possible extensions that will enable significantly larger-scale DTSs.     

Software-Konfigurationsmanagement in großen Softwareprojekten

Zusammenfassung Mit zunehmender Größe der Softwaresysteme verschärfen sich die für die Software-Herstellung typischen Probleme: Beherrschen großer Objektmengen, Erhalten der Systemkonsistenz, Kontrolle der ständigen Änderungseinflüsse und Gewährleisten einer langen Lebensdauer. Die Disziplin Konfigurationsmanagement bildet den methodischen Ansatz, diese Probleme besser zu beherrschen. Software-Konfigurationsmanagement faßt die Herstellung von Softwaresystemen als eine Abfolge von kontrollierten Änderungen an gesicherten Zwischen- und Endergebnissen auf. Dargestellt werden die Objekte und Funktionen des Software-Konfigurationsmanagements sowie die hierfür in großen Software-Projekten benötigten Methoden, Instanzen und Hilfsmittel.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。