A Novel Video Denoising Method with 3D Context Model Based on Surfacelet Transform

本文将3D Context模型应用于Surfacelet变换域,提出一种新的视频去噪方法.Surfacelet变换(ST)是一种新的3D变换,具有多方向分解、各向异性和低冗余度等性质.根据视频信号ST域内系数和噪声分布的特征,将2DContext模型拓展到3D,按照能量分布将ST系数分成多个子块,每个子块有独立的能量和阈值估计.实验结果表明,本文算法噪声抑制效果明显优于分层2D去噪声方法和其它现有的3D方法,去噪视频的PSNR值提高了约2dB.从视觉效果来看,本文算法在去除噪声的同时,能很好的保留视频图像细节,运动物体非常平滑,有效解决传统算法中存在的拖影、闪烁等问题,尤其适合于包含剧烈运动和丰富纹理图像的视频.We propose a novel video denoising method with 3D Context Model in Surfacelet Transform Domain(3DCMST)in this paper.In order to take advantage of the characteristic of the coefficients,the Context model was extended from 2D to 3D.The ST coefficients were divided into several parts according to their energy distribution by 3D Context model and each part had independent energy estimate and threshold.Experimental results show that the proposed method achieves better denoising performance than other 3D or hierarchical 2D denoising methods,and remarkably improves the PSNR of video about 2dB.In terms of visual quality,the proposed method can effectively preserve the video detail,and the trajectory of motion object is very smooth,which is especially adequate to process the video frames with acute movement and plenty of texture.国家自然科学基金(No.60472081);; 航空科学基金(No.05F07001

基于Surfacelet 变换的3D Context 模型视频去噪新方法

本文将3D Context 模型应用于Surfacelet 变换域,提出一种新的视频去噪方法. Surfacelet 变换(ST) 是一种新的3D 变换,具有多方向分解、各向异性和低冗余度等性质. 根据视频信号ST 域内系数和噪声分布的特征,将2D Context 模型拓展到3D ,按照能量分布将ST系数分成多个子块,每个子块有独立的能量和阈值估计. 实验结果表明,本文算法噪声抑制效果明显优于分层2D 去噪声方法和其它现有的3D 方法,去噪视频的PSNR 值提高了约2dB. 从视觉效果来看,本文算法在去除噪声的同时,能很好的保留视频图像细节,运动物体非常平滑,有效解决传统算法中存在的拖影、闪烁等问题,尤其适合于包含剧烈运动和丰富纹理图像的视频. Title: A Novel Video Denoising Method with 3D Context Model Based on Surfacelet Transform 　Abstract : 　We propose a novel video denoising method with 3D Context Model in Surfacelet Transform Domain (3DCMST) in this paper. In order to take advantage of the characteristic of the coefficients ,the Context model was extended from 2D to 3D. The ST coefficients were divided into several parts according to their energy distribution by 3D Context model and each part had independent energy estimate and threshold. Experimental results show that the proposed method achieves better denoising performance than other 3D or hierarchical 2D denoising methods , and remarkably improves the PSNR of video about 2dB. In terms of visual quality ,the proposed method can effectively preserve the video detail ,and the trajectory of motion object is very smooth ,which is especially adequate to process the video frames with acute movement and plenty of texture. Key words : 　video denoising ;Surfacelet transform;3D Context model ; directional filter bank国家自然科学基金(No. 60472081) ;航空科学基金(No. 05F07001

Defects in ⅢNitrides Epilayers

【中文摘要】 采用光荧光和阴极荧光方法 ,对 Ga N外延层中的黄色和蓝色发光进行测量分析 ;同时 ,采用原子力显微镜、扫描电镜及其能谱测量外延层中的缺陷。结果表明 ,黄色和蓝色发光与残留杂质有关。采用第一原理计算结果显示 ,残留 C、O杂质、本征缺陷等是黄色和蓝色的可能物理起源。采用原子力显微镜、扫描电镜、透射电镜及其能谱对 Ga N/Al Ga N异质结中的纳米管进行观测 ,了解了纳米管的形貌。结果表明 ,构成纳米管的小面可能是外延过程中表面吸附引起的 ;计算结果显示 ,纳米管形貌变化与 Ga N/Al Ga N界面处晶格失配应力有关。采用透射电镜观察外延层中沉积物及其周围位错的结构表明 ,沉积物附近应力的存在是位错产生的主要原因 【英文摘要】 Blue and yellow luminescence bands in undoped GaN epilayers were investigated and related to main residual C and O impurities by photoluminescence, which are suggested to be attributable to the electron transitions from O N states to V Ga states and between the inner levels of the C N O N complex, respectively, according to ab initio local density functional calculations. Larger nanopipes in undoped GaN/AlGaN hetero epilayers were imaged as dodecagonal pyramidal indentations, using atomic fo...国家重点基础研究发展规划项目 (批准号 :001CB610505 );国家自然科学基金 (批准号 :69976023、90206030、10134030 );福建省自然 科学基金 (批准号 :A0020001);教育部部分资助项

Image Fusion Algorithm Based on Spatial Frequency-Motivated Pulse Coupled Neural Networks in Nonsubsampled Contourlet Transform Domain

Nonsubsampled contourlet transform (NSCT) provides °exible multiresolution, anisotropy and directional expansion for images. Compared with the original contourlet transform, it is shift-invariant and can overcome the pseudo-Gibbs phenomena around singularities. Pulse Coupled Neural Networks (PCNN) is a visual cortex-inspired neural network and characterized by the global coupling and pulse synchronization of neurons. It has been proven suitable for image processing and successfully employed in image fusion. In this paper, NSCT is associated with PCNN and employed in image fusion to make full use of the characteristics of them. Spatial frequency in NSCT domain is input to motivate PCNN and coe±cients in NSCT domain with large firing times are selected as coe±cients of the fused image. Experimental results demonstrate that the proposed algorithm outperforms typical wavelet-based, contourlet-based, PCNN-based and contourlet-PCNN-based fusion algorithms in term of objective criteria and visual appearance.Supported by Navigation Science Foundation of P. R. China (05F07001) and National Natural Science Foundation of P. R. China (60472081

基于目标约束的NURBS方法凸轮曲线寻优创成设计

针对凸轮机构的设计优化问题,提出了一种通用的NURBS（Non Uniform Rational B-Splines）凸轮曲线寻优创成设计方法,即采用NURBS曲线实现凸轮从动件位移、速度、以及加速度的表达。在约束条件及目标函数的双重限制下,通过数值迭代优化算法对NURBS曲线的控制顶点及权因子进行同步整定以实现凸轮曲线的优化设计与创成,使其满足设计所要求的运动学约束、几何约束、压力角约束、运动不失真条件等综合性能指标。特别地,此方法不仅能够实现优化水平的整体控制,还能够对凸轮运动曲线的局部形状实现自适应调整,使其具有最佳的性能特征。以一DRD（Dwell-RiseDwell）型直动从动件盘型凸轮机构的凸轮曲线设计为例,验证了NURBS凸轮曲线寻优创成设计方法的有效性。应用实例表明,与传统的凸轮曲线设计方法相比,基于目标约束的NURBS方法凸轮曲线寻优创成设计能够在强耦合的约束关系之间,获得目标设计参数最优的凸轮曲线形状表达

乌苏里江国家森林公园规划方案的景观指数辅助评价

通过对比分析景观指数的变化情况 ,评价了乌苏里江国家森林公园总体规划方案的合理性 .计算发现规划前后斑块数从 413减少到 40 1,香农均匀度指数从 0 75 5提高到 0 787,优势度指数从 2 5 5 47减少至 2 4 5 0 0 .景观破碎化程度降低 ,反映廓道特征的r指数、a指数和主要景点之间的景观引力值都有所增加 ,表明规划改善了公园的景观空间结构 ,提高了景观系统的稳定性和风景质量 ,有利于生态环境保护和生态旅游的发展