基于小波非线性外推的图像增强方法

针对图像增强的问题,提出了一种新的图像增强方法．该方法将小波变换与频域非线性外推算法相结合,首先利用小波变换提升图像的高频成分,再利用频域非线性外推算法增加图像的高频分量,最终实现图像的增强．实验表明,该新方法有效地提高了图像的视觉效果．     

电离层层析成像技术与电离层反演

系统介绍了利用电离层层析成像技术进行电离层反演的理论、模型及相应的计算流程.针对电离层层析成像反演算法对初始值比较敏感的特点,提出一种改进算法计算了电离层电子密度剖面,计算结果表明,改进算法可以改善电离层层析成像质量,具有高精度、大空间、实时等优点;最后介绍了电离层层析成像技术应用于电离层预报及地震前兆监测的前景.     

基于小波变换的多分辨率锥束CT图像快速三维重建算法

为了解决FDK重建算法在锥束CT重建中运算量大,耗时较多,以及针对不同的应用环境提供不同分辨率的3维医学图像问题,该文提出一种基于小波变换的多分辨率锥束CT图像快速3维重建算法。首先对采集到的投影图像进行相应尺度的小波变换,得到各尺度小波分解系数,选择相应尺度的小波系数进行FDK重建,可以得到相应低分辨率的3维图像数据,还可根据需要由得到的低分辨率重建数据分别沿着径向取断层图像,进行相应的小波逆变换,进而得到高分辨率的3维图像数据。实验数据表明,该方法不仅能够得到不同分辨率的3维图像数据,而且相较于传统的FDK算法生成分辨率相同、精度相近的高分辨率3维图像数据,重建速度可以提高1倍以上。     

小波变换求解飞秒脉冲光谱相位

介绍应用小波变换方法求解飞秒脉冲的光谱相位。用小波变换对飞秒脉冲光谱干涉条纹作二维时间-频率分析,不需要传统傅里叶变换方法的滤波过程,也消除了滤波引入的噪声,并且具有明显的直观性,脉冲的光谱相位情况可以从小波变换图中直接判断。     

基于小波变换的中波红外偏振图像融合

针对中波红外偏振图像的特征,给出了一种基于小波变换的融合新方法。根据中波红外偏振图像高低频图像特点选择不同的融合规则,针对低频图像采用偏振融合的方法来抑制背景信息,针对高频图像采用超分辨率重建算法来提升细节信息。实验结果显示,证融合后的红外图像比原始图像更加清晰,相较于仅偏振处理图像获得了更高的分辨率,相较于传统小波融合算法增加了偏振方面细节。     

基于Gabor小波变换的机载SAR海面风向反演方法

给出了一种基于Gabor小波变换的机载合成孔径雷达（SAR）海面风向反演的新方法。该方法利用Gabor小波对SAR图像进行二次小波分解,并对小波系数作FFT变换来获取图像谱,其低波数谱连线的垂线方向就是海面风场的风向。利用该方法获得了SAR图像海面风向信息,并与àtrous算法反演结果、浮标测得的海面风向（真值）进行了比较。实验结果表明,采用该方法获得的机载SAR海面风向反演结果与海面浮标实测数据吻合,比àtrous算法有较大改进。     

利用小波降噪的瑞利激光雷达平流层温度反演

介绍了瑞利-拉曼-米散射激光雷达的基本结构与瑞利散射温度反演原理,通过分析对比获得了适合瑞利散射信号的小波分解层数及阈值选取规则,并分别使用小波硬阈值法与软阈值法对信号进行处理,相比而言软阈值法具有更好的降噪效果。利用上述算法反演出南京上空平流层28~46km的温度廓线,将结果与MSISE-90大气模式及AIRS卫星数据进行比对,均表现较好的一致性,验证了小波降噪在瑞利激光雷达温度反演算法中的可靠性。在算法研究的基础上,反演了2009年12月19日19时20分至20时20分连续观测的数据,表明在短时间内平流层温度总体趋势稳定;并对2009年10月至12月的观测数据进行分析处理,得到南京上空平流层月平均温度廓线,表明南京上空的平流层温度在冬季变化不明显。     

基于小波变换的指纹全局方向场重建

从大型指纹库识别不完整或局部指纹仍然是今天的一大挑战。在此文中,我们研究利用小波变换用于指纹方向场重建问题。特别的,我们提出了一种基于小波的多尺度方法从局部的指纹重建全局拓扑表达。然后提出基于结合参数模型和非参数模型来描述重建问题,我们提供了一般表达式可用于所有有效的反变换模型的解决方案。这种方案允许我们分割保护存在的方向场同时预测丢失的未知部分的结构。我们还开发了基于脊线拓扑特征的一些先验信息来估计丢失的方向结构的算法。我们的统计实验表明我们提出的基于模型的算法能有效的恢复指纹的方向场并应用于指纹匹配,这样重大的提高了局部指纹识别其他模块性能。     

一种非线性小波变换在图像压缩中的应用

针对小波变换进行图像压缩过程中重建图像易引起边缘振荡的问题,提出了一种非延拓消除边缘振荡的方法.它通过提升算法与传统的非线性ENO-小波变换结合,把高频分量边缘的能量集中到低频分量上,用小波分量模的极大值对跃变点进行奇异性检测,有效地消除了重建图像引起的边缘振荡.仿真实验表明该方法简单有效.     

一种投影预处理算法在局部CT图像重建中的应用

本文首先对Shepp Logan头颅投影数据低分辨率重建,然后对含噪感兴趣区域相关的投影数据使用一种将小波变换与Wiener滤波相结合的局部投影数据预处理算法进行降噪,最后对降噪后的投影数据局部反投影重建。通过图像平方根误差分析实验结果可知,重建图像相对原图像误差较小。     

Enhanced localized computerized tomography employing the discrete wavelet transform

A new localized computerized tomography technique based on the multiresolution analysis (MRA) implementation of the discrete wavelet transform is proposed. Our technique is based upon viewing the projection data as a set of one-dimensional functions of the space variablet and decomposing each one into an approximation signal and a set of detail signals using MRA. The approximation signal and detiil signals associated with each projection are filtered using the ramp filter || of the standard reconstruction technique filtered back projection to generate the set of filtered projections. It is shown that only a very sparse set of projection data outside of the region of interest (ROI) is required to reconstruct a high-quality image of the ROI and a reasonable image outside of the ROI. Simulation results using the Shepp-Logan head phantom are presented to demonstrate the proposed technique.     

刀口法测平顶光斑和高斯光斑半径的新算法

为了测量平顶光斑和高斯光斑的半径,采用刀口法进行了理论分析和实验验证,并且提出了新的迭代算法。刀口的间距与光斑半径存在正比关系,求出了相应的比例系数。在实际测量中,测得刀口的间距后再乘上相应的系数就可以得到光斑半径。结果表明,将迭代法进行推广,可用于求任意已知强度分布式的光斑半径。     

小波分解和重构的光学可变图像融合研究

针对传统光学可变图像融合方法存在的融合效果差、噪声干扰严重等问题,提出小波分解和重构的光学可变图像融合方法.分析光学可变图像在不同区域的融合原理,获取光学可变图像的特征;采用小波变化的方法,对光学可变图像进行多尺度分解,提取不同频率的小波系数;采用小波阈值降噪方式,对光学可变图像进行降噪处理;通过融合准则选取融合子图像...     

Super-resolution reconstruction based on linear interpolation of wavelet coefficients

High resolution image reconstruction is an image process to reconstruct a high resolution image from a set of blurred, degraded and shifted low resolution images. In this paper, the reconstruction problem is treated as a function approximation. We use linear interpolation to build up an algorithm to obtain the relationship between the detail coefficients in wavelet subbands and the set of low resolution images. We use Haar wavelet as an example and establish the connection between the Haar wavelet subband and the low resolution images. Experiments show that we can use just 3 low resolution images to obtain a high resolution image which has better quality than Tikhonov least-squares approach and Chan et al. Algorithm 3 in low noise cases. We also propose an error correction extension for our method which can lead to very good results even in noisy cases. Moreover, our approach is very simple to implement and very efficient.     

Characterization of NDT signals: Reconstruction from wavelet transform maximum curvature representation

This paper addresses the problem of characterization of the reconstructed non-destructive testing (NDT) signals from a representation in wavelet domain. A novel scheme for characterization of NDT signals from the reconstruction based on wavelet maximum curvature representation has been proposed and stability of the reconstruction from the representation is proved in the paper. It has been established that a signal in the reconstruction set based on wavelet maximum curvature point representation associated with specified non-linear operations removing insignificant information contains complete information for characterization. Data denoising and characterization based on wavelet maximum curvature representation, with a novel dual thresholding scheme, has been presented in this paper. A compression scheme in principal can be designed based on the theory. Analysis of magnetic flux leakage signal has been discussed to illustrate the efficacy of the proposed technique.     

基于小波域的压缩感知超分辨率重建方法

为了提高超分辨率图像的重构效果,提出了一种基于小波域的压缩感知超分辨率重建方法.首先采用小波变换对低分辨率图像进行分解,得到低分辨率图像的低频子带与高频子带,然后采用压缩感知技术分别对低频子带和高频子带进行重建,并通过小波逆变换得到最终重建图像,最后在MATLAB 2012平台上进行仿真实验.结果表明,相对于其他图像重建方法,本文方法的重建图像视觉效果更加理想,不仅提高了低分辨率图像重建精度,而且提高了图像重建效率,可以满足图像处理的实时性、在线性要求.     

莫奈特子波变换分析信号奇点

用原函数为光滑曲线的子波变换(简称莫奈特子波变换)检测信号波形奇点的方法是建立在信号奇异性与李普西兹正则性关系基础上的。该方法的基本原理是信号子波变换Wψ(a,t)等价于信号光滑版s(t)θa(t)的1阶导数,当s(t)θa(t)为尖锐变化时,必然对应其导数的模的极大值,只要检测到子波变换模的极大值,就能检测到信号s(t)的奇点。仿真表明,莫奈特子波变换能准确检测出信号奇点。     

Analog behavioral modeling by multi-companding and wavelet collocation method

In this paper, we develop a wavelet collocation method with multi-companding for behavioral modeling of analog circuits. In the multi-companding procedure, the nonlinear companding algorithm is developed to control the error distribution continuously, while the adaptive scheme is employed to reduce the number of used wavelets. Consequently, the proposed multi-companding algorithm can not only modify the modeling error distribution continuously but also decrease the number of basis functions efficiently. Moreover, the companding function generation is automatic and can be applied for the behavioral modeling of any analog circuits. Jun Tao received the B.S degree in electrical engineering from Fudan University, China, in 2002. Now she is currently working toward the Ph.D. degree in micro-electronic engineering at the Fudan University. Her research interest includes analog behavioral modeling, analog circuit simulation and DFM. Xuan Zeng (M97) received the B.Sc. and Ph.D. degrees in electrical engineering from Fudan University, Shanghai, China, in 1991 and 1997, respectively. She joined the Electrical Engineering Department, Fudan University in 1997 and became a full professor in Microelectronics Department in 2001. Now she serves as the Vice Director of ASIC & System State key Lab. and the Associate Head of Microelectronics Department Fudan University. She was a visiting professor in the Electrical Engineering Department, Texas A&M University, USA and Microelectronics Department of TU Delft, Netherland in 2002 and 2003 respectively. Her research interests include DFM, analog and mixed signal design automation (behavioral modeling, circuit simulation and analog layout generation), high speed interconnect analysis and design and ASIC design. Dr. Zeng received the Cross-Century Outstanding Scholar Award from the Ministry of Education of China in 2002. She was selected into “IT Top 10” in Shanghai China in 2003. She served in the technical program committee of IEEE/ACM ASP-DAC in 2000 and 2005. Dian Zhou received the B.S degree in physics and M.S degree in electrical engineering from Fudan University, China, in 1982 and 1985, respectively, and the Ph.D. degree in electrical and computer engineering from the University of Illinois in 1990. He joined the University of North Carolina at Charlotte as an assistant professor in 1990, where he became an associate professor in 1995. He joined the University of Texas at Dallas as a full professor in 1999, and joined Fudan university as a Changjiang Professor in 2003 (on-leave from the University of Texas at Dallas). Currently, he serves as the dean of Microelectronics School, director of National Key Lab. on ASICs and Systems, and director of Miro-nano-electronics Innovation Platform at Fudan University. His research interests include: High-speed VLSI systems, CAD tools, mixed-signal ICs, and algorithms. Charles Chiang received his Bachelor degrees from the Department of Political Science, Tunghai University at Taichung, Taiwan in 1980, and Department of Computer Science, New Mexico State University, Las Cruces, New Mexico in 1986. Then he had his Masters and Ph.D. degree from the Department of Electrical Engineering and Computer Science, Northwestern University, Illinois in 1988 and 1991, respectively. After working at IBM and EDA companies for 10 years, he joined the Advanced Technology Group at Synopsys, Inc. in 2001. His research interests include routing, placement, floorplan, and signal integrity. His main research focus is now on design for manufacturability (DFM). Dr. Chiang has been a Senior Member of IEEE since 1998. He received the Superior Design Recognition award and the ADAL award from IBM Rochester in 1993 and 1994, respectively. He is one of the top 15 winners with new patent filing in 2005 and 2006 in Synopsys. He has served on the technical committee of ICCAD from 2004 to 2006, on that of Field Programming Logic (FPL) from 2002 to 2003, as well as on the committee of ASP-DAC in 2007. He has published more than 40 technical papers and filed 10 US patents.     

用于信号特征提取和重建的脊提取算法

该文论述了以信号在连续小波变换域上形成的脊作为信号特征进行信号的特征提取和信号重建的方法,并且将该理论应用到话音信号的处理中。仿真实验表明,对于最高频率为4kHz的语音信号来说,提取3～5条脊即可以很好地刻划信号的全部信息,重建的信号在主观感觉上达到了较好的效果。     

Despeckling of medical ultrasound images using Daubechies complex wavelet transform

The paper presents a novel despeckling method, based on Daubechies complex wavelet transform, for medical ultrasound images. Daubechies complex wavelet transform is used due to its approximate shift invariance property and extra information in imaginary plane of complex wavelet domain when compared to real wavelet domain. A wavelet shrinkage factor has been derived to estimate the noise-free wavelet coefficients. The proposed method firstly detects strong edges using imaginary component of complex scaling coefficients and then applies shrinkage on magnitude of complex wavelet coefficients in the wavelet domain at non-edge points. The proposed shrinkage depends on the statistical parameters of complex wavelet coefficients of noisy image which makes it adaptive in nature. Effectiveness of the proposed method is compared on the basis of signal to mean square error (SMSE) and signal to noise ratio (SNR). The experimental results demonstrate that the proposed method outperforms other conventional despeckling methods as well as wavelet based log transformed and non-log transformed methods on test images. Application of the proposed method on real diagnostic ultrasound images has shown a clear improvement over other methods.