An immune oriented multi-agent system for biological image processing

In this article, we present a parallel image processing system based on the concept of reactive agents. Our system lies in the oRis language, which allows to describe finely and simply the agents’ behaviors to detect image features. We also present a method of segmentation using a multi-agent system, and two biological applications made with oRis. The stopping of this multi-agent system is implemented through a technique issued from immunology: the apoptosis.     

小波提升算法及其在图像处理中的应用

小波提升算法是一种新的双正交小波构造方法，通过预测算子，确定高频信息，并初步确定低频信息，然后通过更新算子，对初步确定的低频信息进行修正，从而确定低频信息。它在空域对信号进行变换，完成了对信号频域的分析。在图像处理中，基于离散小波变换的提升算法比传统的卷积算法运算简单，实时性好，易于实现，因而被新一代图像压缩标准JPEG2000所采用。文中简要介绍了小波提升算法的原理，分析了其特点，并介绍了JPEG2000标准中采用的W5／3、D9／7两种小波的提升格式和实现算法。     

320×240 Pixels CMOS Digital Image Sensor with Wide Dynamic Range

A 320×240 CMOS image sensor is demonstrated,which is implemented by a standard 0.6 μm 2P2M CMOS process.For reducing the chip area,each 2×2-pixel block shares a sample/hold circuit,analog-to-digital converter and 1-b memory.The 2×2 pixel pitch has an area of 40 μm×40 μm and the fill factor is about 16%.While operating at a low frame rate,the sensor dissipates a very low power by power-management circuit making pixel-level comparators in an idle state.A digital correlated double sampling,which eliminates fixed pattern noise,improves SNR of the sensor, and multiple sampling operations make the sensor have a wide dynamic range.     

一种基于TV模型的自适应图像修复方法

图像修复是数字图像处理的重要内容，可用于被损坏的图像和视频修复、视频文字去除以及视频错误隐藏等。基于TV模型的修复方法有较好的恢复效果，但对参数的选取比较敏感，且运算量较大。本文提出了一种基于TV模型的自适应图像修复方法，与原方法相比可以有效提高该算法的稳健性，并能显著的减少运算时间。     

Frequency domain identification of Wiener models

This paper proposes a frequency domain algorithm for Wiener model identifications based on exploring the fundamental frequency and harmonics generated by the unknown nonlinearity. The convergence of the algorithm is established in the presence of white noise. No a priori knowledge of the structure of the nonlinearity is required and the linear part can be nonparametric.     

Linear predictive transform of monochrome images

Digital monochromatic images are encoded using a novel minimum mean square error (MSE) linear predictive transform (LPT) coding formulation. The new formulation is appealing for two important reasons. First, it leads to simple coder implementation with a satisfactory signal-to-noise ratio (SNR). Second, it provides a general theoretical framework from which minimum MSE predictive coding and minimum MSE transform coding arise as special cases. Some specific results of this paper that illustrate the previous ideas are: a simple and generally suboptimum two-dimensional LPT coder operating at 2 bit pixer⁻¹ has approximately one third the complexity of a 4 × 4 Hadamard coder while yielding a better SNR; an optimum 2D LPT coder operating at 2 bit pixer⁻¹ has approximately one sixth the complexity of a 4 × 4 Karhunen-Loeve transform (KLT) coder while yielding a better SNR.     

A fuzzy clustering algorithm enhancing local model interpretability

In this work, simple modifications on the cost index of particular local-model fuzzy clustering algorithms are proposed in order to improve the readability of the resulting models. The final goal is simultaneously providing local linear models (reasonably close to the plant’s Jacobian) and clustering in the input space so that desirable characteristics (regarding final model accuracy, and convexity and smoothness of the cluster membership functions) are improved with respect to other proposals in literature. Some examples illustrate the proposed approach.     

河流工程中的图形绘制与处理

在河流工程领域,不管是实体模型还是数学模型,对多样化的数据和丰富多彩的图形的需要越来越强烈,旧的表现形式已经被层出不穷的新的、信息量大而且地位高的2D、3D图形所取代,因此在工程中合理地选择绘图方式和开发软件就变得十分重要。以实际操作经验为基础,从基本操作类到二次开发类再到高端图形图像开发类,详细地讨论了在河流工程中各种图形的绘制和处理方法选择,具有一定参照价值。     

红外背景干扰研究

根据从许多地区收集来的录象磁带上的图象数据和大量红外图象数据，对红外背景图象内的干扰进行了研究。图象内的噪声是以象元电平为单位的均方根形成计算。图象经过空间滤波处理，对其内的干扰再进行计算。为获得关于红外背景图象的空间频率构成的信息，在滤波和非滤波两种状态下计算了图象的光谱密度，把计算出的干扰值输入数据库取出多组数据并绘图，确定参数量（如天气、背景类型和测量条件等）对干扰电平的影响。