An extension of the Shannon theory approach to cryptography

Shannon's information-theoretic approach to cryptography is reviewed and extended. It is shown that Shannon's random cipher model is conservative in that a randomly chosen cipher is essentially the worst possible. This is in contrast with error-correcting codes where a randomly chosen code is essentially the best possible. The concepts of matching a cipher to a language and of the trade-off between local and global uncertainty are also developed.     

Digital color imaging

This paper surveys current technology and research in the area of digital color imaging. In order to establish the background and lay down terminology, fundamental concepts of color perception and measurement are first presented using vector-space notation and terminology. Present-day color recording and reproduction systems are reviewed along with the common mathematical models used for representing these devices. Algorithms for processing color images for display and communication are surveyed, and a forecast of research trends is attempted. An extensive bibliography is provided.     

Interference in the learning of circuit theory

Commonly introductory texts on circuit theory present in tandem the loop and node formulations of the equilibrium equations, and show how these relate to each other through the duality principle. Whereas this approach understandably appeals to those already well versed in basic definitions (voltage, current, impedance, admittance, etc.), evidence exists that the early undergraduate is confused by this approach. Trying to learn at one time multiple concepts that are so very similar in some ways, but different in others, appears to increase the conceptual difficulty of the material rather strikingly. This paper reports two experiments with college sophomores. Both show that intermingling of dual concepts leads to serious interference in learning. It is suggested that students should master thoroughly one set of principles for solving circuit problems before the dual set is presented. This suggestion conforms with the approach exemplified by the older texts on circuit theory.     

色域及色域覆盖率

阐述非均匀色度空间及均匀色度空间、色域及色域覆盖率的基本概念,用色域覆盖率度量SDTV和HDTV电视机显示终端、LCD和DLP前投或背投影接收机等彩色还原能力,并给出了色域覆盖率测量示例.     

基于光谱重建技术的壁画颜色复原与评价

为了在给定的照明和观察条件下，用相机响应信号重建物体表面光谱反射率，实现颜色的高精度复原，采用了多光谱成像技术采集物体表面的多光谱图像，使用主成分分析、 R 矩阵和正则化 R 矩阵方法进行了光谱反射率重建的理论研究，并对壁画色块颜色复原进行了实验验证，取得了壁画色块的重建光谱和颜色复原数据，同时对基于正则化 R 矩阵方法的壁画色块颜色复原结果进行了评价。结果表明，正则化 R 矩阵方法进行光谱重建的光谱精度和色度精度更高，与主成分分析和 R 矩阵方法相比，色差降低了0.0732，适应度系数提高了1.10%，均方根误差降低了0.0035，光谱匹配偏指数降低了0.0225。该方法能够满足高精度颜色再现的需要，适用于文物艺术品数字化存档、文物艺术品修复等领域。     

Color imaging for multimedia

To a significant degree, multimedia applications derive their effectiveness from the use of color graphics, images, and video. However, the requirements for accurate color reproduction and for the preservation of this information across display and print devices that have very different characteristics and may be geographically apart are often not clearly understood. This paper describes the basics of color science, color input and output devices, color management, and calibration that help in defining and meeting these requirements     

计算彩色彩虹全息术颜色复现机理分析

基于颜色传递和匹配原理,讨论了彩色计算全息色系和计算机显示色系下颜色量的一般转换关系,同时研究了计算全息物光波振幅和其对应的颜色量之间的等色传递问题,建立了计算全息物光波振幅与计算机显示色系下颜色量之间所应满足的关系。在此基础上对计算彩色彩虹全息术颜色复现机理进行了详细的讨论,给出了计算彩色彩虹全息术颜色复现时的三原色。     

基于遗传算法的天线匹配网络研究

遗传算法是模拟生物进化过程而发展起来的一种优化和搜索求解极值问题的自组织、自适应的人工智能技术,其通过对一组编码进行简单的遗传操作和优胜劣汰来指导学习和确定进化的方向.遗传算法提供了一种求解非线性、多模型、多目标等复杂系统优化问题的通用框架.利用遗传算法针对天线匹配网络的设计进行研究,并利用安捷伦科技有限公司的ADS软件针对同一天线设计匹配网络,通过仿真结果证明利用遗传算法设计天线匹配网络的可行性与可靠性.     

基于Colibri配色软件的迷彩斑点颜色复制技术

针对传统迷彩斑点颜色的特点,指出人工配色方法存在的不足,并说明了利用计算机配色软件-colibri对采集的背景颜色进行计算机配色的实施方法及步骤,对所得配方进行有针对性的修正,获得与背景颜色的光谱反射曲线基本相同的配方的光谱反射曲线,并列出CIE Lab图表.通过对比可以看出,它们之间基本达到了同谱同色,符合在可见光波段的迷彩要求.     

Reconstruction of Images Distorted by Defocusing and Blurring without Determining the Type and Parameters of the Hardware Function

Journal of Communications Technology and Electronics - Abstract—A new approach to solving the problems reconstructing images distorted by defocusing and blurring is proposed. It is shown that...     

Space-dependent color gamut mapping: a variational approach.

Gamut mapping deals with the need to adjust a color image to fit into the constrained color gamut of a given rendering medium. A typical use for this tool is the reproduction of a color image prior to its printing, such that it exploits best the given printer/medium color gamut, namely the colors the printer can produce on the given medium. Most of the classical gamut mapping methods involve a pixel-by-pixel mapping and ignore the spatial color configuration. Recently proposed spatial-dependent approaches for gamut mapping are either based on heuristic assumptions or involve a high computational cost. In this paper, we present a new variational approach for space-dependent gamut mapping. Our treatment starts with the presentation of a new measure for the problem, closely related to a recent measure proposed for Retinex. We also link our method to recent measures that attempt to couple spectral and spatial perceptual measures. It is shown that the gamut mapping problem leads to a quadratic programming formulation, guaranteed to have a unique solution if the gamut of the target device is convex. An efficient numerical solution is proposed with promising results.     

改进蚁群算法求解多属性双边稳定匹配问题

从稳定匹配的角度研究多属性双边匹配问题,介绍多属性双边稳定匹配问题的概念和定义,给出多属性匹配度的定义和排序方法,建立了针对稳定匹配结果的评价函数和评价规则,在此基础上提出了蚁群算法求解此问题的思路及适合此类问题求解的蚂蚁状态转移策略和信息素更新策略,同时给出算法步骤。仿真结果表明,改进的蚁群算法能够有效求解传统稳定匹配问题以及多属性双边稳定匹配问题。     

On ratio-based color indexing

The color ratio approach to indexing has been found to be robust and effective in indexing image and video databases, in different color spaces, and when using transformed color features, such as those from the Karhunen-Loeve transform (KLT) or the discrete cosine transform (DCT). However, the reason for the superior performance of the color ratio model, especially on different color spaces or with transformed color features has, at best, been speculative. This paper develops a generalized form for the color ratio model, based on which we characterize the general distribution of the color ratios. From the distribution, we present a theory that explains and supports the performance of the color ratio approach in image and video indexing. It is shown that the same theory accounts for its effectiveness in different color spaces and in the transform domain. Some general problems encountered in using the original retinex lightness algorithm, and some other issues specific to ratio-based color indexing are discussed in the light of the theory. Results are presented which show that the proposed theory is supported by empirical evidence.     

跨媒体复现中CIECAM02背景预测性能评价

为了研究跨媒体复现中CIECAM02的背景预测性能,基于双目同时的视觉匹配实验,获得显示器软拷贝与不同中性灰背景下硬拷贝的视觉匹配数据,分析了中性灰背景对颜色外貌的影响,并利用实验数据对CIECAM02的背景预测性能做了评价.实验结果表明:背景明度主要诱导色块明度和彩度的变化,对色相略有影响.明度、彩度、色相三者中,明度改变最明显,背景越暗,诱导色块越亮,随着背景明度变暗,背景明度的诱导绝对量趋于稳定;彩度变化幅度不大,但是不符合色诱导规律;而色相基本不变.CIECAM02可以解释背景明度对明度的诱导现象,但不能解释对彩度的诱导现象,且背景参数不能准确反映背景对颜色的影响,有待于修正.     

一种解决约束优化问题的模糊粒子群算法

该文针对复杂约束优化问题,提出了一种模糊粒子群算法(FPSO),设计了一个新的扰动算子,在此基础上定义了模糊个体极值和模糊全局极值,利用这两个定义改进了粒子群进化的方程,利用该方程更新粒子的速度与位置,可以避免早熟收敛问题;定义了不可行度阈值,利用此定义给出了新的粒子比较准则,该准则可以保留一部分性能较优的不可行解微粒。用概率论的有关知识证明了算法的收敛性。仿真结果表明,对于复杂约束优化问题,算法寻优性能优良,特别是对于超高维约束优化问题,该算法获得了更高精度的解。     

一种基于标准色块与多项式拟合的CRT色彩管理新模型

CRT显示器的色彩管理是彩色图像复制的关键技术之一.本文在分析CRT显色原理的基础上,提出了一种新的CRT色彩管理模型.该算法将CRT的RGB色空间、CIEXYZ色空间和三色传感器驱动值之间的关系转换为两两关系分别求取.最后用本文的转换模型得到的X、Y、Z计算值与实际测量值进行比较,以及用本文算法与普通多项式拟合算法和三维查找表算法得到的色彩转换精度比较,均表明转换模型具有较为满意的转换精度.     

Matching Structures by Computing Minimal Paths on a Manifold

The general problem of matching structures is very pervasive in computer vision and image processing. The research presented here tackles the problem of object matching in a very general perspective. It is formulated for the matching of surfaces. It applies to objects having small or large deformation and arbitrary topological changes. The process described hinges on a geodesic distance equation for a family of curves or surfaces embedded in the graph of a cost function. This geometrical approach to object matching has the advantage that the similarity criterion can be used to define the shape of the cost function. Matching paths are computed on the cost manifolds using distance maps. These distance maps are generated by solving a general partial differential equation which is a generalization of the geodesic distance evolution scheme introduced by R. Kimmel, A. Amir, and A. F. Bruckstein (1995, IEEE Trans. Pattern Anal. Mach. Intell.17, 635–640). An Eulerian level-set formulation is also introduced, leading to a numerical scheme used for solving partial differential equations originating from hyperbolic conservation laws, which has proven to be very robust and stable.     

Adaptive integrated image segmentation and object recognition

The paper presents a general approach to image segmentation and object recognition that can adapt the image segmentation algorithm parameters to the changing environmental conditions. Segmentation parameters are represented by a team of generalized stochastic learning automata and learned using connectionist reinforcement learning techniques. The edge-border coincidence measure is first used as reinforcement for segmentation evaluation to reduce computational expenses associated with model matching during the early stage of adaptation. This measure alone, however, cannot reliably predict the outcome of object recognition. Therefore, it is used in conjunction with model matching where the matching confidence is used as a reinforcement signal to provide optimal segmentation evaluation in a closed-loop object recognition system. The adaptation alternates between global and local segmentation processes in order to achieve optimal recognition performance. Results are presented for both indoor and outdoor color images where the performance improvement over time is shown for both image segmentation and object recognition     

Data fusion: color edge detection and surface reconstructionthrough regularization

Data fusion provides tools for solving problems which are characterized by distributed and diverse information sources. In this paper, the authors focus on the problem of extracting features such as image discontinuities from both synthetic and real images. Since edge detection and surface reconstruction are ill-posed problems in the sense of Hadamard, Tikhonov's regularization paradigm is proposed as the basic tool for solving this inversion problem and restoring well-posedness. The proposed framework includes: (1) a systematic view of oneand two-dimensional regularization; (2) extension of the standard Tikhonov regularization method by allowing space-variant regularization parameters; and (3) further extension of the regularization paradigm by adding multiple data sources to allow for data fusion. The theoretical approach is complemented by developing a series of algorithms, then solving the early vision problems of color edge detection and surface reconstruction. An evaluation of these methods reveals that this new analytical data fusion technique output is consistently better than each of the individual RGB edge maps, and noisy corrupted images are reconstructed into smooth noiseless surfaces     

An Adaptive Feature-fusion Method for Object Matching over Non-overlapped Scenes

Object matching in non-overlapped scenes of multi-cameras is a challenging task, due to a large number of factors, e.g. complex backgrounds, illumination variance, pose of observed object, viewpoint and image resolutions of different cameras, shadows and occlusions. For an object, matching its observations with variant appearances in such context usually turns to evaluate their similarity over some sophisticatedly chosen image features. We observe that certain feature is usually robust to certain variance, e.g. SIFT is robust to the variance in viewpoint and scale. We mean that incorporating the abilities of a bag of such features would reach a better performance. Based on these observations and insights, we propose an adaptive feature-fusion algorithm. The algorithm, first, evaluates the matching accuracy of four sophisticatedly chosen and well validated features: color histogram, UV chromaticity, major color spectrum and SIFT, using exponential models of entropy as similarity measure. Second, an adaptive fusion algorithm is presented to fuse a bag of features for a collaborative similarity measure. Our approach is shown to be able to adaptively and dynamically reduce the variances of object appearances caused by multiple factors. Experimental results show that our approach applied to human matching reaches a high robustness and matching accuracy in comparison with the previous fusion methods.