医学超声图像处理系统

超声图像诊断是与X线CT、同位素扫描、核磁共振等一样重要的医学图像诊断手段。根据肝脏超声图像进行脂肪肝的诊断,是病变确诊的主要方法。但是,与CT和核磁共振等医学图像相比,超声图像的图像质量较差,目前的诊断以定性为主,受主观因素影响较大。以图像分割为基础,以VC语言为工具,建立了超声图像处理系统,对超声图像进行了二值化处理,并对处理结果进行了量化,为诊断提供了依据。     

一种基于小波系数重要图编码的图像压缩算法

提出了一种新的基于小波系数重要图编码的图像压缩算法。该算法根据量化后的波系数的特点进行了一种期望排序，然后舍掉序列后面大量的零值小波系数，从而得到一个波系数子集，能以少的小波系数来很好地逼近原始图像，省去了零树编码中零树结构带来的大量比特开销。实验表明，该算法与MPEG-4的静止图像压缩算法相比较，重构图像的峰值信噪比（PSNR）值在相同码率下有较大的提高。     

像增强型夜视系统的图像信息传递

在分析了像增强夜视系统信息传递的基础上，指出像增强器输出端荧光屏至人眼的图像传递过程，构成了像增强夜视系统信息传递量的限制．提出了采用系统信息传递量作为夜视系统设计与评价的方法，利用这种方法可以发现在像增强器增益足以补偿光谱选道衰减的条件下，采用彩色像增强可以大幅度增加夜视系统传输的信息量．     

一种全局运动的图像处理算法研究

在摄像机进行航拍的图像处理系统中,由摄像机运动所引起的视频运动,背景变化是主要特点。在进行图像采集时,每个像素都在变化,采用传统的图像编码方式进行图像压缩,压缩效果比较差。提出了基于块分割的精确运动估计算法,它是一种很好的图像压缩方法。     

物体内部三维位移场分析的数字图像相关方法

提出了物体内部三维位移场的数字图像相关分析方法，对物体变形前后，或连续变形的两个相邻状态的内部三维结构的数字图像，通过相关运算获得三维位移场.文中给出了三维相关法的体搜索窗口、相关函数及亚像素运算的相关系数拟合函数.数字模拟结果证明了三维相关法的正确性及可靠性.位移计算精度为0.02像素. 关键词： 数字图像相关 三维相关 亚像素     

An Effective Software Pipelining Algorithm for Clustered Embedded VLIW Processors

This paper proposes a software pipelining framework, CALiBeR (ClusterAware Load Balancing Retiming Algorithm), suitable for compilers targetingclustered embedded VLIW processors. CALiBeR can be used by embedded systemdesigners to explore different code optimization alternatives, that is, high-qualitycustomized retiming solutions for desired throughput and program memory sizerequirements, while minimizing register pressure. An extensive set of experimentalresults is presented, demonstrating that our algorithm compares favorablywith one of the best state-of-the-art algorithms, achieving up to 50% improvementin performance and up to 47% improvement in register requirements. In orderto empirically assess the effectiveness of clustering for high ILP applications,additional experiments are presented contrasting the performance achievedby software pipelined kernels executing on clustered and on centralized machines.     

Image processing using cellular neural networks based on multi-valued and universal binary neurons

Multi-valued and universal binary neurons (MVN and UBN) are the neural processing elements with the complex-valued weights and high functionality. It is possible to implement an arbitrary mapping described by partially defined multiple-valued function on the single MVN. An arbitrary mapping described by partially defined or fully defined Boolean function, which can be non-threshold, may be implemented on the single UBN. The quickly converging learning algorithms exist for both types of neurons. Such features of the MVN and UBN may be used for solving the different problems. One of the most successful applications of the MVN and UBN is their usage as basic neurons in the Cellular Neural Networks (CNN). It opens the new effective opportunities in nonlinear image filtering and its applications to noise reduction, edge detection and solving of the super resolution problem. A number of experimental results are presented to illustrate the performance of the proposed algorithms.An erratum to this article can be found at     

N指标d维广义Wiener过程象集的m项代数和的几个性质

设珮犠（狋）：犚犖＋ →犚犱是犖指标犱维广义Ｗｉｅｎｅｒ过程，对任意紧集犈１，…，犈犿犚犖＞ ，该文研究了犿项代数和珮犠（犈１）…珮犠（犈犿）的Ｈａｕｓｄｏｒｆｆ维数，Ｐａｃｋｉｎｇ维数和正的Ｌｅｂｅｓｇｕｅ测度及内点的存在性． 其结果包含并推广了布朗单的结果．