Poisson image fusion based on Markov random field fusion model

In this paper, we present a gradient domain image fusion framework based on the Markov Random Field (MRF) fusion model. In this framework, the salient structures of the input images are fused in the gradient domain, then the final fused image is reconstructed by solving a Poisson equation which forces the gradients of the fused image to be close to the fused gradients. To fuse the structures in the gradient domain, an effective MRF-based fusion model is designed based on both the per-pixel fusion rule defined by the local saliency and also the smoothness constraints over the fusion weights, which is optimized by graph cut algorithm. This MRF-based fusion model enables the accurate estimation of region-based fusion weights for the salient objects or structures. We apply this method to the applications of multi-sensor image fusion, including infrared and visible image fusion, multi-focus image fusion and medical image fusion. Extensive experiments and comparisons show that the proposed fusion model is able to better fuse the multi-sensor images and produces high-quality fusion results compared with the other state-of-the-art methods.     

A new image fusion performance metric based on visual information fidelity

Because subjective evaluation is not adequate for assessing work in an automatic system, using an objective image fusion performance metric is a common approach to evaluate the quality of different fusion schemes. In this paper, a multi-resolution image fusion metric using visual information fidelity (VIF) is presented to assess fusion performance objectively. This method has four stages: (1) Source and fused images are filtered and divided into blocks. (2) Visual information is evaluated with and without distortion information in each block. (3) The visual information fidelity for fusion (VIFF) of each sub-band is calculated. (4) The overall quality measure is determined by weighting the VIFF of each sub-band. In our experiment, the proposed fusion assessment method is compared with several existing fusion metrics using the subjective test dataset provided by Petrovic. We found that VIFF performs better in terms of both human perception matching and computational complexity.     

Multiconsensus of second order multiagent systems with directed topologies

A novel multiconsensus problem is introduced in multiagent systems. The states of multiple agents in each subnetwork asymptotically converge to a consistent value with information exchanges among subnetworks. The multiconsensus problem of second order multiagent systems with directed topologies is studied. Three linear protocols are proposed to solve the multiconsensus problem. Necessary and sufficient conditions are derived based on matrix theory. Simulations are provided to demonstrate the effectiveness of the theoretical results.     

Statistically uniform intra-block refresh algorithm for very low delay video communication

This paper focuses on the mechanism underlying the overall delay of a real-time video communication system from the time of capture at the encoder to the time of display at the decoder. A detailed analysis is presented to illustrate the delay problem. We then describe a statistically uniform intra-block refresh scheme for very low delay video communication. By scattering intra-blocks uniformly into continuous frames, the overall delay is significantly decreased, and object changes in the scene could be presented to the end user instantly. For comparison, the overall delay and the peak signal-to-noise ratio (PSNR) performance are tested. The experiment results show that an average of approximately 0.1 dB PSNR gain on average is obtained relative to random intra-macroblock refresh algorithm in H.264 JM, and the end-to-end delay performance is significantly improved.     

缩短BCH编码应用于无线传感网络的能效分析

基于能效分析了具有不同纠错能力的缩短BCH码在典型的无线传感器网络模型中的优劣.仿真结果表明,在典型应用中,缩短汉明码可以取得整体上最优的效果,并可通过对信息码长的调节取得最大能效,在对网络可靠性要求非常严格的情况下,可考虑使用纠错能力为2位或3位的缩短BCH码.     

计算机应用现状及发展趋势

人类步入信息时代以后,计算机和人类的关系也显得日益密切.人们的生活、生产以及科学研究都离不开计算机.在这个计算机飞速发展的年代,我们应该了解计算机应用的现状以及它的发展趋势.     

Collapse-free thermal bonding technique for large area microchambers in plastic lab-on-a-chip applications

Bonding is an essential step to form microchannels or microchambers in lab-on-a-chip applications. In this paper, we present a novel plastic thermal bonding technique to seal and form large area microchambers (planar characteristic width and length on the order of 1 mm and characteristic thickness on the order of 10–100 μm) without collapse by introducing a holed pressure equalizing plate (HPEP) that includes holes of the same size and shape as the microchambers. To demonstrate the proposed technique, two types of large area microchambers [(1) 20 × 10 mm and 40 μm thick and (2) 12 × 2.5 mm and 120 μm thick] with microchannels were designed and replicated on plastic substrates by means of hot embossing and injection molding processes with prepared two nickel mold inserts. The replicated large area microchambers as well as the microchannels in the plastic lab-on-a-chip were successfully sealed (i.e., no leakage) and formed without any collapse by the proposed thermal bonding technique with the help of the HPEP.     

基于FPGA实现DSP与RapidIO网络互联

本文首先简单的介绍了总线的发展,从而引出一种新型的串行点对点交换结构RapidIO.DSP在高性能处理系统中的重要性毋庸置疑,但是目前的很多DSP并没有RapidlO接口.本文提出了利用FPGA,将DSP的总线桥接到一个RapidIO IP上,从而实现了DSP与RapidIO网络的互联.     

基于模板的SoC结构自动划分方法

针对SoC芯片设计中的系统划分问题,提出一种面向应用的系统结构自动划分方法--基于模板的系统划分方法,并开发了系统划分工具--TBPS.基于模板的系统划分方法通过提取应用描述中的相似结构,并使用相似结构划分系统,最终得到一个尽量复用的系统结构.系统的相似结构划分采用遗传算法实现最优覆盖的搜索,并使用贪婪算法实现资源配置和任务调度.与已有的在系统划分中事先设定目标结构方法不同,文中方法可以根据应用的特点自动生成划分的结构.采用该方法及TBPS实现了应用描述到系统结构的自动划分.实验结果表明了TBPS对数据处理为主的应用划分的有效性.     

蚁群算法及其在路由优化中的应用综述

蚁群算法(ACO)是一类新型的机器学习技术,根据蚁群算法的正反馈原理和启发式原理的特点,针对目前国内国际的研究情况,对蚁群算法在最优路径的搜寻上从收敛性,收敛算法的改进以及收敛速度等方面的研究分别进行了分析综述,并对蚁群算法的一些应用,如:LEO卫星网络和无线传感等方面进行了阐述.对蚁群算法在路由优化和负载平衡上的研究进行了对比分析,发现了它们存在的不足,指出了在该领域需要进一步研究的热点问题.