基于稀疏特性的盲二值图像去模糊

通过分析二值图像发现其像素值具有稀疏特性,因此采用L₀梯度反卷积算法结合二值图像的组合特性来处理盲二值图像的复原问题。常见的图像复原方法均将二值图像看作灰度值图像来处理,当其考虑到二值图像的特殊性质时,将会针对这种特定类型的图像得到更好的复原效果。提出的盲复原算法基于一阶梯度空间L₀最小化问题的框架,利用L₀梯度图像平滑方法来获得明显的图像边缘以估计模糊核,并将二值图像的特有属性作为正则项加入目标函数。在图像的复原过程中,通过二值图像先验来强制复原结果趋于二值图像。根据提出的模型,给出了基于稀疏特性的盲二值图像复原算法。通过实验将该算法与传统的盲反卷积复原算法进行比较,结果表明所提算法具有良好的性能,对二值图像进行复原是有效的。     

混合非凸非光滑正则化约束的模糊图像盲复原

为能够复原出高质量的清晰图像,提出一种混合正则化约束的模糊图像盲复原方法。首先,根据模糊核的稀疏性,采用L₀范数的正则项对模糊核进行稀疏约束,以提高模糊核估计的准确性;然后,根据图像梯度的稀疏性,采用混合一阶和二阶图像梯度的L₀范数对图像梯度进行正则化约束,以保留图像边缘信息;最后,由于所提出的混合正则化约束模型本质上是非凸非光滑优化问题,通过交替方向乘子法对模型进行求解,并在非盲反卷积阶段采用L₁范数数据拟合项和全变分的方法复原清晰图像。实验结果表明,所提方法能够复原出更加清晰的细节和边缘信息,复原结果的质量更高。     

空间尺度信息的运动模糊核估计方法

运动模糊核的准确估计是实现单幅运动模糊图像盲复原成功的关键.但是,因为不能准确提取出有利的图像边缘以及简单的正则化约束项的设计,导致现有运动模糊核（motion blur kernel,简称MBK）的估计并不十分准确,存在瑕疵.因此,为了能够估计出准确的运动模糊核,提出了一种基于空间尺度信息的运动模糊核估计方法.首先,为了准确地提取有利的图像边缘,移除有害的图像结构,提出了一种基于图像空间尺度信息的图像平滑模型,实现有利图像边缘的准确快速提取;然后,从运动模糊核的内在特性出发,将空间域的L₀范数和梯度域的L₂范数结合到一起,提出了一种正则化约束模型,很好地保证了运动模糊核的稀疏平滑特性,并结合之前提取出的有利的图像边缘,共同实现运动模糊核的准确估计;最后,采用一种半二次性分裂的交互式最优化策略对提出的模型进行最优化求解.在客观的评价指标和主观的视觉效果上进行了大量实验,其结果证明所提出的方法能够估计出更准确的MBK和复原出更高质量的去模糊图像.     

混合特性正则化约束的运动模糊盲复原

目的 为了提高运动模糊图像盲复原清晰度,提出一种混合特性正则化约束的运动模糊盲复原算法。方法 首先利用基于局部加权全变差的结构提取算法提取显著边缘,降低了噪声对边缘提取的影响。然后改进模糊核模型的平滑与保真正则项,在保证精确估计的同时,增强了模糊核的抗噪性能。最后改进梯度拟合策略,并加入保边正则项,使图像梯度更加符合重尾分布特性,且保证了边缘细节。结果 本文通过两组实验验证改进模型与所提算法的优越性。实验1以模拟运动模糊图像作为实验对象,通过对比分析5种组合步骤算法的复原效果,验证了本文改进模糊核模型与改进复原图像模型的鲁棒性较强。实验结果表明,本文改进模型复原图像的边缘细节更加清晰自然,评价指标明显提升。实验2以小型无人机真实运动模糊图像为实验对象,通过与传统算法进行对比,对比分析了所提算法的鲁棒性与实用性。实验结果表明,本文算法复原图像的标准差提升约11.4%,平均梯度提升约30.1%,信息熵提升约2.2%,且具有较好的主观视觉效果。结论 针对运动模糊图像盲复原,通过理论分析和实验验证,说明了本文改进模型的优越性,所提算法的复原效果较好。     

可学习高阶微分方程的图像盲复原

目的 图像盲复原是图像处理中的常见的重要问题之一,具有巨大的研究价值和广泛的应用。通常情况下,相机抖动,聚焦不准,环境噪声等因素都会造成图像模糊。由于图像盲复原需要同时求解模糊核和清晰图像,导致该问题是病态的而难于求解。现有的盲复原方法可以分为两大类,一类是基于最大后验概率来同时估计潜在图像和模糊核的方法,但是这样耦合在一起的方法由于先验条件和初值设置不恰当,常常会导致最终求得的是问题的平凡解,以至于盲复原的效果并不理想。另一类是基于变分贝叶斯来估计模糊核,这种方法通常是采用最大化强边图像的边缘概率,由此估计的模糊核鲁棒性较强,但是对潜在图像的强边条件要求比较高,计算复杂度和实现难度都较大。鉴于以上方法的优缺点,提出基于高阶微分方程学习的方法来实现图像去模糊。方法 借鉴传统的迭代演化方法和网络学习方法各自的优势,将网络学习到的特征（引导图像,卷积滤波器,稀疏测度）融入到高阶微分方程的演化过程中区,提出可学习的基于高阶微分方程的演化来模拟图像的演化过程。具体地,先用范数约束得到一个粗略的强边引导图像,然后将学习到的卷积滤波器和稀疏函数一起作用在当前的潜在图像上,得到一个关于图像的更好的梯度下降方向,将此作为微分方程演化的一个步骤,得到一个更为精炼的强边图像。最后用精炼的强边图像来估计模糊核。该方法可以通过先验知识和训练数据来有效地控制模糊核的估计,进而得到较为清晰的盲复原结果。结果 在图像建模层面上,用非盲复原的方法验证了本文提出的微分方程演化过程是可行的。通过和其他盲复原方法做对比,在不同的基准图像数据库上的定量的实验中,本文方法在数据库上的峰值信噪比,结构相似度分别达到30.30,0.91,误差率低至1.24;比其他方法的结果都要好,在时间上,虽然我们的算法不是用时最少的,但是和性能相当的本文的方法相比,本文算法时间消耗远比该算法少。在各种不同类型的模糊图像去模糊结果也表明了本文方法是有效的。结论 本文可学习的高阶微分方程去模糊的方法,能够有效地估计模糊核,进而更好地恢复出清晰图像。实验结果表明本文方法在各种场景中具有较高的灵活性,都能自适应地对图像去模糊。     

基于正则化方法的图像盲去模糊

针对标准化稀疏先验的正则化方法估计复杂模糊核时的不准确性, 引入图像的预处理, 提出了一种图像盲去模糊的新方法。该方法将图像盲去模糊分为三个步骤：利用双边滤波器和冲击滤波器对图像进行预处理, 使得图像的噪声降低、边缘突出, 有利于模糊核的估计; 对预处理后的图像, 利用基于标准化稀疏先验的正则化方法估计模糊核; 根据估计出的模糊核利用TV正则化方法对图像进行非盲去卷积。采用快速迭代收缩阈值算法和快速总变分图像复原算法分别求解模糊核估计模型和图像非盲去卷积模型。实验结果表明, 针对单幅模糊图像, 该方法可以估计出准确的模糊核, 对噪声具有鲁棒性, 并且提高了图像复原速度, 具有较好的图像恢复效果。     

加强边缘感知的盲去模糊算法

目的 拍摄过程中,如果摄像机进行了错误的聚焦,就会得到模糊的图像,如何将模糊图像变得清晰成为一个亟待解决的问题。目前关于图像的去模糊方法多采用基于模糊核约束的卷积模型。但是由于实际应用中很难准确获取模糊核的信息,同时计算机也存在精度限制,计算结果与实际物理模型有偏差,因而去模糊的主要挑战为：如何精确地估计模糊核,以及如何在复原过程中减弱由于精度限制造成的振铃效应。方法 振铃效应是指图像的灰度剧烈变化处产生的震荡,类似于钟被敲击后产生的波状空气震荡。在图像复原过程中,此效应通常发生在梯度变化较大的边缘区域附近。本文对此进行研究,在去模糊过程中引入边缘信息作为约束条件,以改善模糊核的估计,并通过抑制边缘区域的反卷积,抑制图像复原过程中的振铃效应。算法主要分为如下3个部分：1）设计了适用于模糊图像的边缘提取算法;2）利用边缘信息设计了加强边缘感知的反卷积算法;3）提出并设计了安全检测子,以保证算法在边缘区域复原的完整性。结果 实验结果表明,在没有先验知识的情况下,本文方法可以较好地恢复图像细节,并有效抑制振铃效应。较之传统的去模糊处理算法,本文方法在性能上有较大提高。比如,相比于Chan、Krishnan以及Hu的方法,本文方法在峰值信噪比指标上分别提高了25.73%、3.52%和4.43%,在结构相似性指标上分别提高了7.67%、1.63%和3.59%。同时,与基于深度学习的方法相比,本文方法不依赖于数据集,鲁棒性更强。结论 本文方法可以较好地恢复图像细节,并抑制振铃效应,同时比深度学习方法适用范围更广。     

基于稀疏表示和结构自相似性的单幅图像盲解卷积算法

图像盲解卷积研究当模糊核未知时,如何从模糊图像复原出原始清晰图像.由于盲解卷积是一个欠定问题,现有的盲解卷积算法都直接或间接地利用各种先验知识.本文提出了一种结合稀疏表示与结构自相似性的单幅图像盲解卷积算法,该算法将图像的稀疏性先验和结构自相似性先验作为正则化约束加入到图像盲解卷积的目标函数中,并利用图像不同尺度间的结构自相似性,将观测模糊图像的降采样图像作为稀疏表示字典的训练样本,保证清晰图像在该字典下的稀疏性.最后利用交替求解的方式估计模糊核和清晰图像.模拟和真实数据上的实验表明本文算法能够准确估计模糊核,复原清晰的图像边缘,并具有很好的鲁棒性.     

一种混合的单图像去运动模糊方法

图像的盲恢复一直是数字图像处理领域的难点,对运动模糊图像的复原进行研究,提出了一种混合的单图像去运动模糊方法。首先估计PSF,然后利用PSF和原始模糊图像评估潜像,并对边缘恢复、模糊核估计和反卷积进行多次迭代,采用自适应非盲反卷积方法得到高质量的去模糊图像。最后,与维纳滤波、露西-理查德森这两种经典算法的实验效果进行比较。实验结果表明,本算法保持细节的能力强,去模糊效果更好。     

基于稀疏表示和梯度先验的图像盲去模糊

针对目前基于稀疏表示的图像盲卷积算法细节恢复有限等问题,提出一种基于稀疏表示和梯度先验的图像盲卷积算法。虽然每个图像块可以通过字典稀疏表示,但是图像块重构出的图像常常出现“伪像”,本文将梯度先验知识和超拉普拉斯先验知识融入稀疏表示盲卷积模型中,采用迭代方法交替估计中间清晰图像和模糊核,一旦获得模糊核,采用超拉普拉斯非盲去卷积算法恢复出最终的清晰图像。实验结果表明,与其他去模糊算法相比,本文算法在抑制振铃方面效果显著。     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

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。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

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.     

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.     

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。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.