压缩感知在医学图像压缩中的应用

调研压缩感知的数学理论基础和常用方法,包括稀疏变换、测量矩阵和重构算法,利用Matlab软件实现压缩感知实验,比较几种测量矩阵的性能,提出双阈值分块正交匹配追踪重构算法。根据图像不同区域信息量的不同,采取分块处理的方法并加入采样阈值,针对不同子图像块采取不同采样率,提高采样效率;加入判断阈值,降低重构效果对采样阈值的依赖。实验结果表明,该方法能够以较低的采样率实现较高的重构精度,使压缩感知在医学图像压缩方面得到了较好应用。     

基于DFT基的矿井视频监控图像分块压缩感知方法

针对矿井视频监控图像受噪声干扰影响大,采用常规的图像采样和压缩方法存在图像模糊和传输时间过长等问题,提出了一种矿井视频监控图像分块压缩感知方法。该方法通过建立矿井视频监控图像分块压缩感知模型,在井下图像采集节点利用稀疏随机矩阵进行压缩采样,然后在地面监控中心利用正交匹配追踪( OMP )算法重构图像。研究结果表明,采用本文算法的重构图像误差小、重构时间短,所需信号采样点数少;与扰频Hadamard矩阵相比,采用稀疏随机矩阵和高斯随机矩阵作为观测矩阵对图像信号重构的峰值信噪比( PSNR)提高4 dB~5 dB;本文算法与基于小波基的算法相比,信号重构的PSNR提高1 dB~4 dB,重构时间缩短至少80％以上。     

基于小波树模型的CoSaMP压缩感知算法

无线传感网络存在网络带宽限制和传感器节点的能耗问题,实际应用中通常希望可以通过重构算法从采集的少量数据中还原出原始信息,压缩感知理论为上述问题提供了一个解决思路。利用压缩感知理论,对无线传感器网络中温度传感器的监测信号进行了压缩感知的应用研究。针对传统压缩采样匹配追踪(CoSaMP)算法中测量次数多、重构精度低等问题,利用信号的小波系数所形成的连通树的结构特性,提出了基于小波树模型的压缩采样匹配追踪算法。将该算法应用到无线传感器网络监测信号的压缩感知仿真实验中,与传统压缩采样匹配追踪算法的重构性能进行比较,结果表明该算法较传统压缩采样匹配追踪算法在一定范围内对无线传感器网络中的温度信号具有更好的压缩感知性能。     

二维逐步正交匹配追踪算法

在图像等二维信号的应用与处理上,常规压缩感知理论框架存在重构算法效果差、图像块效应明显、对噪声敏感等问题。针对这些问题,根据现有二维观测模型和二维重构算法设计思想,可以设计一种新的重构算法：二维逐步正交匹配追踪算法。该算法借鉴了相关一维重构算法的设计思想,通过每次迭代选取符合阈值条件的多列原子进而正交化处理的步骤,提升了重构效率,改善了恢复图像质量。理论分析和实验结果表明,提出的算法在重构时间得到控制的情况下,得到的图像信噪比有较大提升,超越了现有典型的二维重构算法。     

一种改进的压缩感知重构算法

压缩感知重构信号时,在感知过程中如何选定支撑集对算法的重构性能至关重要.基于压缩采样匹配(CoSaMP)重构算法,引入Dice系数匹配性度量准则,优化了支撑集的选择.上述算法改进了从给定的观测矩阵中挑选与残差信号最匹配原子的匹配准则,体现了残差信号中各个元素对原子选取的重要作用.仿真结果表明:在同等稀疏的条件下,重构算法与传统的CoSaMP算法相比,误差低于传统CoSaMP算法,且随着观测维数的增加,重构信号的平均成功概率比传统的CoSaMP算法的大,实现了较小的重构误差和更好的压缩性能.     

基于二次筛选的回溯广义正交匹配追踪算法的稀疏信号重构

压缩感知是一种新型的信号采样及重构理论,高效的信号重构算法是压缩感知由理论转向实际应用的枢纽。为了更精确地重构出原始稀疏信号,本文提出一种基于二次筛选的回溯广义正交匹配追踪算法。首先采用内积匹配准则选出较大数目的相关原子,提高原子的利用率。其次利用广义Jaccard系数准则对已选出的原子进行二次筛选,得到最匹配的原子,优化原子选取方式。实验结果表明,在不同稀疏度和观测值下进行信号重构,相比于回溯广义正交匹配追踪算法、正交匹配追踪算法及子空间追踪算法,本文算法在重构误差及重构成功率方面有较大的优越性。     

基于双阈值的压缩采样匹配追踪改进算法

针对基于压缩感知的压缩采样匹配追踪(CoSaMP)算法迭代次数严重依赖于信号稀疏度,候选原子冗余度大,从而导致最终的支撑原子集选择时间长、选择精度低等问题,提出一种基于双阈值的压缩采样匹配追踪算法.该算法利用模糊阈值进行支撑集候选原子的选择,引入残差与观测矩阵的相关度变化阈值作为迭代停止条件,对图像进行重构.仿真实验表明,所提出的算法重构速度快,重构效果优于CoSaMP算法.     

一种改进的图像分块压缩感知模型

分块压缩感知用于图像获取可以解决传统压缩感知在重构时运算量大的问题,但是运用分块压缩感知却使重构图像的质量有所降低。提出了一种改进的图像分块压缩感知算法。该算法通过对观测矩阵加权,保证了图像低频部分在重构时获得更大的精度,提高了图像的质量。另外,算法根据各图像块不同纹理复杂性,自适应地改变观测值数目,使得在保证图像质量的前提下,重构所需的总观测值数目更少。实验证明了该算法的有效性。     

图像自适应分块的压缩感知采样算法

目的 在图像压缩感知过程中,不管是整体采样还是固定分块采样,都不能充分利用图像的稀疏性,存在采样率与图像重构质量的矛盾。提出了一种基于图像纹理变化的自适应分块感知采样算法ABCS(adaptive block compressed sensing),再结合JPEG量化思想,在不降低图像重构质量的前提下降低采样率,更大地提高压缩比。方法 首先进行图像预分块,计算分析各块纹理复杂度,当图像块纹理复杂度低于相应阈值,选择最佳采样率对各块观测采样,当图像块纹理复杂度高于相应阈值,需再分块,重复上述步骤,达到最小16×16块时停止分块。当最小块的纹理复杂度高于最大阈值采用JPEG量化编码,其他块选择匹配的采样率,以压缩感知方式压缩。结果 ABCS算法与典型的压缩感知重构算法结合并与其原始算法比较,在相近采样率条件下,图像重构质量提高明显,尤其在低采样率下性能更佳,如20%采样率下重构图像PSNR值达到30 dB左右。结论 提出的自适应的分块采样充分利用图像的稀疏分布,提高压缩感知的效率;高复杂纹理块采用JPEG编码处理,避免了重构质量差的缺点,同时减少了重构时间。     

基于Kent混沌测量矩阵的压缩感知图像重构算法

图像重构是图像数字化和恢复高质量图像信号的关键技术,使用压缩感知理论进行图像重构的意义在于显著减少采样次数,降低系统资源的消耗。测量矩阵的构造是压缩感知的重要研究内容之一。提出一种基于Kent混沌测量矩阵的压缩感知图像重构算法,将Kent混沌序列作为测量矩阵,采用离散小波变换的稀疏化方法,在小波域对原始图像信号进行测量。最后采用正交匹配追踪方法恢复原始图像。仿真实验中,对比高斯随机测量矩阵和Logistic混沌测量矩阵,对不同的图像进行重构。实验结果证明,基于Kent混沌测量矩阵的重构算法能够恢复原始图像,重构性能优于高斯随机观测矩阵和Logistic混沌测量矩阵,同时克服了随机测量矩阵硬件难以实现的缺陷。     

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.