To improve the quality of low illumination image, based on DT-CWT and tone mapping, an image enhancement algorithm is proposed. First, the RGB image is converted into the HSV color space whose lumi-nance component V will be divided into high and low frequency sub-bands by DT-CWT. The high-frequency sub-band is processed by Butterworth filter to enhance the image details and suppress the noise while the low-frequency sub-band is managed by the improved tone mapping to adjust the image illumination. Finally, DT-CWT inverse transformation is applied to obtain the reconstructed V component which is synthesized with the H and S components to obtain a clear RGB image. In this paper, we make full use of excellent characteris-tics of accurate image-detail expression of DT-CWT which is combined with the improved tone mapping algo-rithm based on Retinex theory to achieve the enhancement of low illumination image. The experiment results show that the proposed algorithm can obviously improve the visual effect of the low illumination color image.

A multi-wavelet system with detailed mathematical expression called V-system is introduced.The infrared and visible images are decomposed into different layers and orientations by using multi-resolution of V-system and multi-orientation in non-subsampled contourlettransform(NSCT).And then different fusion strategies were adopted to fuse raw images in each layer and each orientation respectively.Firstly,the original image was decomposed by multilevel V-decomposition,and contour informations and multi-layer detailed informations of images were gotten;then the obtained contour informations were decompose again by NSCT to obtain low frequency and high frequency coefficients.The low frequency coefficients are fused according to the strategy based on sparse representation,and the high frequency coefficients are fused according to the strategy based on 2D Log-Gabor energy,and then the improved pulse coupled neural network was used to fuse multi-layer detailed information.Finally,the fused image is obtained by the corresponding inverse transformation.The algorithm decomposes images in different layers and orientations to obtain more refined detail of raw images.The combination of various fusion strategies makes the detailed information more clear and enhances the contrast of the fused images,and it also improves the objective indicators observably.

Fused images obtained using the traditional multi-modal medical image fusion technology cannot express details clearly and lesion obviously.In view of this,a new fusion method which combines the V-transform and Nonsubsampled Contourlet Transform(NSCT) is proposed.The source images are first decomposed into contour sub-image and detail sub-images by applying the multi-layer V-decomposition,and then NSCT transform is performed on the contour sub-image.Fusion rule in NSCT domain is designed.Fusion strategy for detail information is presented on detail sub-images.The fused image is finally obtained by overlaying the fused contour image and fused detail image together.Experimental results show that the proposed algorithm outperforms the traditional discrete wavelet transform and NSCT transform in both visual effect and evaluation indexes.

机器人在教育领域的应用正在展现出越来越广阔的前景,无论是机器人技术发达的美国还是人口众多的中国内地,对此都进行了很多探索和实践.机器人在教育领域的应用面临很多复杂问题,教育机器人的资源需要不断开发,应用模式需要持续创新,应用领域需要积极拓宽,本文将结合作者多年来的探索与实践,对机器人在教育领域的应用进行阐述.

把U-正交变换应用到图像无损编码中,研究U-正交矩阵的基本三角可逆矩阵(TERM)分解与单行基本可逆矩阵(SERM)分解.一个N阶U-正交矩阵的TERM分解由N-1个自由变量决定,用区间收缩方法可以搜索到TERM分解的局部近似最优解.如果用行交换方法搜索正交矩阵的SERM分解,那么一个8阶的正交矩阵最多只有40320种可能的SERM分解,用穷举法即能找到SERM的近似最优分解.最后,用U-正交矩阵的可逆分解对图像进行无损编码,实验表明可逆U-正交变换的无损编码的码率与浮点U-正交变换的近似无损编码的码率基本相同,SERM分解要比TERM分解更有效,三次U-正交变换的编码效果与离散余弦变换的编码效果几乎完全相同.因此,在图像无损编码中,可用三次U-正变变换代替DCT.

A CAD software system named FDE2009 (FPGA Development Environment) is introduced to be applied to modern hierarchical FPGAs.This system consists of a complete CAD flow of software modules including technology mapping,placement,routing,bit file generator and programming.According to the feature of hierarchical modern FPGAs,we’ve introduced the idea of logical layer in placement and a bottom-up way to build routing resource graph,in order to enhance the utilization efficiency of logical resources and reduce the runtime of our system.A documentary system with extendable tags is also defined and integrated in FDE2009,which allows the system to digest information for further development.Co-operational testing of both software and hardware system shows the correctness,efficiency,and practicality of FDE2009,and gives a stable result of the co-operation between FDP2009 software system and the corresponding FPGA chips.

为了提高FPGA布线资源的灵活性,提出一种通过扩大布线资源图的最小环来设计布线资源的方法.首先分析了布线资源图的最小环大小和布线资源中信号传播灵活性的关系,并通过调整布线资源中线网的连接结构来扩大该最小环.采用该方法设计了一种新的开关盒结构--最小环最大化(MLM)开关盒.实验数据表明,MLM开关盒与4种学术上典型的开关盒结构--Disjoint,Universal,Wilton和JSB相比,在时序上处于平均水平,而布通率分别提高了17. 7%,8. 0%,2. 4%和2. 2%.

提出按像素的灰度值作图像区域非均匀剖分的思想,并利用这种思想实现了一种信息伪装算法.视像素的灰度值为拟合数据,用最小二乘法作数据拟合,得到数字图像的自适应非均匀剖分算法,并以图像的非均匀三角剖分为例给出了详细剖分过程.将保密图像的三角剖分信息用四进制数记录,并对公开的数字图像作相同的剖分,将剖分信息及保密图像的灰度信息隐藏于公开的图像中,利用三角形剖分下图像的重构,即得到一种图像信息伪装新算法,其突出优点在于极大地降低了编码和解码的时间.通过不同类型图例的实验,表明带隐藏数据的伪装图像不易被察觉带有隐藏信息, 并且重构图像的质量较好,是一种可行的信息伪装新算法.

In this paper, we present a new design of a switch box of an FPGA that requires less channel width than conventional designs in routing the same circuit. The design, called a Minloop switch box, is based on the method of minimum-loop-size maximization in routing resources. Experimental results show that the Minloop switch box requires 17.7%, 8.0% and 2.4% less channel width than the classic fabric of Disjoint, Universal and Wilton switch boxes, respectively.