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无压边拉深凹模成形曲面的优化  [PDF]
王孝培,李集仁
重庆大学学报 , 1990,
Abstract: 利用优化方法对拉深凹模成形曲面进行研究,建立含有工件稳定条件为约束的优化模型。其优化解可以避免工件起鼓,保证具有最小的F_(max)和得到最大的拉深比。
Recent Progress in Image Deblurring  [PDF]
Ruxin Wang,Dacheng Tao
Computer Science , 2014,
Abstract: This paper comprehensively reviews the recent development of image deblurring, including non-blind/blind, spatially invariant/variant deblurring techniques. Indeed, these techniques share the same objective of inferring a latent sharp image from one or several corresponding blurry images, while the blind deblurring techniques are also required to derive an accurate blur kernel. Considering the critical role of image restoration in modern imaging systems to provide high-quality images under complex environments such as motion, undesirable lighting conditions, and imperfect system components, image deblurring has attracted growing attention in recent years. From the viewpoint of how to handle the ill-posedness which is a crucial issue in deblurring tasks, existing methods can be grouped into five categories: Bayesian inference framework, variational methods, sparse representation-based methods, homography-based modeling, and region-based methods. In spite of achieving a certain level of development, image deblurring, especially the blind case, is limited in its success by complex application conditions which make the blur kernel hard to obtain and be spatially variant. We provide a holistic understanding and deep insight into image deblurring in this review. An analysis of the empirical evidence for representative methods, practical issues, as well as a discussion of promising future directions are also presented.
双纵模窄线宽光纤拉曼放大器  [PDF]
许将明,冷进勇,吴武明,周朴,侯静
强激光与粒子束 , 2011,
Abstract: ?报道了一台实现了双纵模窄线宽激光输出的光纤拉曼放大器。利用中心波长1079.7nm的双纵模窄线宽种子激光器获得了频率间隔1.4ghz、功率比约3∶1的双纵模输出,各纵模的线宽约为10mhz;再利用1031nm泵浦光对双纵模种子光进行拉曼放大,实现了1.07w双纵模激光输出。拉曼放大过程中,两个纵模的线宽、频率间隔及功率比保持得很好。
融合多平台dinsar数据解算拉奎拉地震三维同震形变场  [PDF]
王永哲,李志伟,朱建军,胡俊
武汉大学学报(信息科学版) , 2012,
Abstract: ?针对单一平台dinsar技术仅能获取雷达视线方向同震形变场的问题,根据雷达成像的几何条件,融合不同轨道、不同平台的dinsar数据解算了拉奎拉地震的三维同震形变场。三维形变结果反映的拉奎拉地震发震断层的特征与地质调查的结果较吻合。将得到的三维形变场数据与该地区gps观测站数据进行比较,结果表明,得到的拉奎拉地震的三维同震形变场比较可靠且精度较高。
p-π共轭分子的氨基面外弯曲振动模的拉曼光谱  [PDF]
陶莎,于利娟,吴德印,田中群
物理化学学报 , 2013,
Abstract: 拉曼光谱是一种用途广泛的无损分子检测技术,其能够提供化学物质的分子结构指纹信息.一种面外弯曲振动模被称作wagging振动,它的信号尤为特殊,其频率和强度都非常依赖于检测环境.以乙烯胺和苯胺为例,采用密度泛函理论计算研究了p-π共轭分子分别与水簇和银簇作用的平衡结构、成键作用和拉曼光谱.结果表明,弱相互作用,如分子与金属表面的弱吸附作用以及分子与水之间的氢键作用,均使氨基面外弯曲振动模(ωnh2)的拉曼信号发生显著的变化.考虑溶剂化效应后,氢键作用减弱,计算拉曼光谱趋于一致.通过进一步对电子结构的分析,解释了面外弯曲振动信号显著增强的原因,揭示了面外弯曲振动模与分子p-π共轭作用之间的关系.
应用改进欧拉算法解算磁性目标空间位置参数  [PDF]
卞光浪,翟国君,刘雁春,黄谟涛,欧阳永忠
测绘学报 , 2011,
Abstract: 指出了目前磁性目标探测中常规欧拉方法存在的局限性,提出在欧拉窗口内视地磁场和其它目标干扰异常联合影响为线性变化,将构造指数作为动态变化参数代入欧拉方程一并求解,并利用多元线性回归方法解决了欧拉方程非线性问题。在质量控制方案中,根据构造指数和目标深度变化规律,给出了离散欧拉解滤波措施;采用层次聚类分析方法对滤波后欧拉解进行分类,其思路为基于距离判断准则,对欧拉解进行了初次分类,用检验法判定各簇是否来源于同一总体,以修正初次分类结果,经过淘汰含欧拉解数目较少的簇后,剩余各簇位置参数的重心则对应磁性目标空间位置。通过球体与长方体仿真试验以及实测数据验证表明给定相关阈值参数后,实现了欧拉方法全自动反演,磁性目标空间位置参数具有很高解算精度,噪声对目标平面位置解算结果基本上没有影响,但对深度解算结果存在一定影响。
解算变位齿轮啮合方程的诺模图法
刘亚南
光子学报 , 1983,
Abstract: 在设计、加工和检验变位齿轮时,经常需要解算变位齿轮啮含方程。在一些著作中1-5]给出了ξ_0—λ_0—Б_0函数表,在简化该方程的计算上起了很大的作用。近年来,在一些著作和文献中2-3]、6-9]又先后发表了几种解算这个方程的图算法。在保证必要的计算精度的条件下,这种方法要比利用ξ_0—λ_0—Б_0函数表更为方便,特别是对变位齿轮的设计提供了一个很好的工具。本文给出了一种新的解算变位齿轮啮合方程的图算法——平行图尺诺模图法,同时举例说明了利用这个诺模图所能解决的一些重要问题。 本文附图5幅,参考文献12种。
Generalized Video Deblurring for Dynamic Scenes  [PDF]
Tae Hyun Kim,Kyoung Mu Lee
Computer Science , 2015,
Abstract: Several state-of-the-art video deblurring methods are based on a strong assumption that the captured scenes are static. These methods fail to deblur blurry videos in dynamic scenes. We propose a video deblurring method to deal with general blurs inherent in dynamic scenes, contrary to other methods. To handle locally varying and general blurs caused by various sources, such as camera shake, moving objects, and depth variation in a scene, we approximate pixel-wise kernel with bidirectional optical flows. Therefore, we propose a single energy model that simultaneously estimates optical flows and latent frames to solve our deblurring problem. We also provide a framework and efficient solvers to optimize the energy model. By minimizing the proposed energy function, we achieve significant improvements in removing blurs and estimating accurate optical flows in blurry frames. Extensive experimental results demonstrate the superiority of the proposed method in real and challenging videos that state-of-the-art methods fail in either deblurring or optical flow estimation.
Dictionary Learning for Deblurring and Digital Zoom  [PDF]
Florent Couzinie-Devy,Julien Mairal,Francis Bach,Jean Ponce
Computer Science , 2011,
Abstract: This paper proposes a novel approach to image deblurring and digital zooming using sparse local models of image appearance. These models, where small image patches are represented as linear combinations of a few elements drawn from some large set (dictionary) of candidates, have proven well adapted to several image restoration tasks. A key to their success has been to learn dictionaries adapted to the reconstruction of small image patches. In contrast, recent works have proposed instead to learn dictionaries which are not only adapted to data reconstruction, but also tuned for a specific task. We introduce here such an approach to deblurring and digital zoom, using pairs of blurry/sharp (or low-/high-resolution) images for training, as well as an effective stochastic gradient algorithm for solving the corresponding optimization task. Although this learning problem is not convex, once the dictionaries have been learned, the sharp/high-resolution image can be recovered via convex optimization at test time. Experiments with synthetic and real data demonstrate the effectiveness of the proposed approach, leading to state-of-the-art performance for non-blind image deblurring and digital zoom.
Adaptive Motion Detection for Image Deblurring in RTS Controller  [PDF]
SANDEEP MISHRA,ABANIKANTA PATTANAYAK,RADHANATH PATRA,SUBHRAJIT PRADHAN
International Journal of Innovative Research in Science, Engineering and Technology , 2013,
Abstract: An Adaptive method for Image Deblurring is presented here. Processing of image data collected from both surveillance camera and on road traffic control motor vehicle camera is a big issue because often the objects are in motion and sometimes both the objects and camera are not steady. This leads to Blurring of the image and further image processing is not possible due to the degradation of received image. So Image Deblurring techniques are applied before enhancement or further processing. But it needs proper data for Deblurring like the frequency characteristics (Point Spread Function (PSF)) and Noise characteristics (Noise-to-Signal Power Ratio(NSR)). The method presented here gives the above information along with the motion information. The information about motion detection is very important because in the Deblurring process the noise estimation cannot be done without knowing actual pixels of the sensor noise present in the image. So to get a deblurred image with proper noise reduction that can be further processed in the RTS (Road Traffic & Safety) controller required information are provided sequentially according to the motion detection and Deblurring algorithm. This method uses some good Deblurring methods like Blind Deconvolution and Regularization filtering along with proper motion detections and characteristics estimations to get an image close to the true image which is sufficient for further processing.
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