Disparity-based just-noticeable-difference model for perceptual stereoscopic video coding using depth of focus blur effect

Human 3D perception provides an important clue to the removal of redundancy in stereoscopic 3D (S3D) videos. Because objects outside the binocular fusion limit cannot be fused on retina, the human visual system (HVS) makes them blur according to the depth-of-focus (DOF) effect to increase the binocular fusion limit and suppress diplopia, i.e. double vision. Based on human depth perception, we propose a disparity-based just-noticeable-difference model (DJND) to save bit-rate and improve visual comfort in S3D videos. We combine the DOF blur effect with conventional JND models in the pixel domain into DJND. Firstly, we use disparity information to get the average disparity value of each block. Then, we integrate the DOF blur effect into luminance JND (LJND) by a selective low pass Gaussian filter to minimize the visual stimulus in S3D videos. Finally, we incorporate disparity information into the filtered JND models to obtain DJND. Experimental results demonstrate that the proposed method successfully improves both image quality and visual comfort in viewing S3D videos without increasing the bit-rate.     

Syntactic compression codes at the zero entropy point

Syntactic compression codes compress the tree, which is the syntax of a binary source message. The ones considered here originate from image processing. The syntactic trees usedhave a constant valency and their binary labels distinguish whether the source substring derived from a node is completely zero or not. We compress them simply by deleting some redundant subtrees.

These codes fall into a theoretically new class of codes which is wider than the classical ones. They are here studied in the neighborhood of a zero of the binary entropy function. There, their behavior is close to that of an infinite run length encoding and the optimum valency is three. Finally, we open a problem, related with automata theory, which perhaps could provide a further link between Information Theory and Algorithmic Information Theory.     

虚拟士兵的智能记忆模型研究

为了提高虚拟士兵的真实度与可信度,在分析现有研究成果的基础上,依据生物记忆原理和遗忘特性,提出了一种智能记忆模型.构造了记忆信息的编码形式,建立了基于槽式和广义树结构的记忆分层存储模型；提出了带有参数的遗忘算法,并运用宽度优先算法,实现了记忆信息的搜索和调用.借助Matlab工具对算法进行了验证,验证结果表明该算法与实际情况基本相符.     

面向自适应码流的渐进编码方法的研究

多媒体信息呈几何级数的爆炸性增长,带来海量信息的同时也带来庞大的数据量,加重了网络的负担,同时不同用户对所要接收图像的质量要求有所不同,如果以相同的标准进行处理势必会造成一定程度上信息的浪费。文章对静止图像的渐进编码作了进一步的研究,对基本层和增强层采用不同的编码策略,更加适应网络复杂多变的带宽条件。文章还通过与用户之间的交互式操作来满足用户不同的需求。实验结果表明,在压缩效果达到JPEG压缩标准的情况下,增强了渐进功能,更加适应网络需要。     

Lattice Vector Quantization Applied to Speech and Audio Coding

Lattice vector quantization(LVQ) has been used for real-time speech and audio coding systems.Compared with conventional vector quantization,LVQ has two main advantages:It has a simple and fast encoding process,and it significantly reduces the amount of memory required.Therefore,LVQ is suitable for use in low-complexity speech and audio coding.In this paper,we describe the basic concepts of LVQ and its advantages over conventional vector quantization.We also describe some LVQ techniques that have been used in speech and audio coding standards of international standards developing organizations(SDOs).     

Improved macroblock level rate control for the spatially scalable extension of H.264/AVC

An improved rate control algorithm, designed for scalable video coders incorporating interlayer prediction, is proposed. Firstly, a Rate Distortion (RD) model for interlayer prediction involving the spatial enhancement layers is devised. An optimised Mean Absolute Difference (MAD) prediction model for the spatial enhancement layers that considers both the MAD from the spatial base layer in the same frame and the MAD from the corresponding macroblock in previous frames is also proposed. Simulation results show that the resulting algorithm produces accurate rate control with an average bit rate error of less than 0.26%. Compared with the JVT-W043 default rate control algorithm of the JSVM, the proposed algorithm improves the average PSNR by up to 0.53 dB or reduces the bit rate by an average of 10.95%. Furthermore, the proposed algorithm can be combined with the existing rate control scheme for H.264/AVC, resulting in further improvements.     

传真通信中MMR编码译码的实现

MMR编码技术是传真通信在发送端对图像进行分解、处理、调制，而在接收端进行解调、处理和传真图像合成而采用的一种编码方法，通过基本的软件语言来实现MMR编码与译码的基本功能。     

Interval analysis applied to the maximum loading point of electric power systems considering load data uncertainties

This paper proposes a simple and efficient power flow method to calculate, in an interval manner, the main variables corresponding to the maximum loading point, under load data uncertainties. The resulting interval nonlinear system of equations is solved using Krawczyk method. The proposed methodology is implemented in the Matlab environment using the Intlab toolbox. Results are compared with those obtainable by Monte Carlo simulations. IEEE 30 bus system and a South-southeastern Brazilian network are used to validate the proposed methodology.     

Capacity Region of a Class of Gaussian Cognitive Degraded Broadcast Channel

This paper studies the cognitive broadcast channel in which the primary user com- municates to the primary receiver, while the secondary user has noncausal knowledge of the primary radio＇s codeword and expects to communicate to two secondary receivers. Comparing with the existing cognitive radio channel which considers only one secondary receiver, cognitive broadcast channel studies the case that there are multiple secondary receivers. To this end, we investigate the fundamental limits of the performance of the Gaussian cognitive broadcast channel from the information theoretic perspective. Specifically, we derive the capacity region of the Gaussian cognitive degraded broadcast channel with weak interference.