Digital Filtering of Weakly Structured UV/VIS Spectra of Inorganic Compounds

Band-pass and Variable digital filters as well as Savitzky-Golay derivatization method have been investigated and compared with the method of selfdeconvolution. The combination of the band-pass filtering and least-squares band fit optimization technique has been proposed as an efficient tool of analysis of vibronically structured electronic absorption spectra of inorganic compounds.     

A novel modified cepstral based technique for blind estimation of motion blur

In the problem of blind image deconvolution, estimation of blurring kernel is the first and foremost important step. Quality of restored image highly depends upon the accuracy of this estimation. In this paper we propose a modified cepstrum domain approach combined with bit-plane slicing method to estimate uniform motion blur parameters, which improves the accuracy without any manual intervention. A single motion blurred image under spatial invariance condition is considered. It is noted that the fourth bit plane of the modified cepstrum carries an important cue for estimating the blur direction. With the exploration of this bit plane no other post processing is required to estimate blur direction. The experimental evaluation is carried out on both real-blurred photographs and synthetically blurred standard test images such as Berkeley segmentation dataset and USC-SIPI texture image database. The experimental results show that the proposed method is capable of estimating blur parameters more accurately than the existing methods.     

Blind motion deblurring using multiple images

Recovery of degraded images due to motion blurring is a challenging problem in digital imaging. Most existing techniques on blind deblurring are not capable of removing complex motion blurring from the blurred images of complex structures. One promising approach is to recover the clear image using multiple images captured for the scene. However, in practice it is observed that such a multi-frame approach can recover a high-quality clear image of the scene only after multiple blurred image frames are accurately aligned during pre-processing, which is a very challenging task even with user interactions. In this paper, by exploring the sparsity of the motion blur kernel and the clear image under certain domains, we propose an alternative iteration approach to simultaneously identify the blur kernels of given blurred images and restore a clear image. Our proposed approach is not only robust to image formation noises, but is also robust to the alignment errors among multiple images. A modified version of linearized Bregman iteration is then developed to efficiently solve the resulting minimization problem. Experiments show that our proposed algorithm is capable of accurately estimating the blur kernels of complex camera motions with minimal requirements on the accuracy of image alignment. As a result, our method is capable of automatically recovering a high-quality clear image from multiple blurred images.     

Gradient-Based Blind Deconvolution with Phase Spectral Constraints

This paper proposes a new blind deconvolution method with additional phase spectral constraints for a blurred image. A degradation of an original image is mathematically modeled by a convolution of an original image and a point-spread function (PSF). The proposed method consists of the following three steps: (i) projection onto a complex set satisfying the phase spectral constraint in a frequency space; (ii) minimization of a cost function preserving the constrained phase spectra; and (iii) projection onto an image space satisfying nonnegative and support constraints. This method restores both the original image and the PSF with high accuracy. The effectiveness of the proposed method is verified by applying it to some blind deconvolution problems for digital images, and the experimental results show that the performance is superior to the conventional blind deconvolution methods.     

Abstract Inverse Estimation with Application to Deconvolution on Locally Compact Abelian Groups

Recovery of the unknown parameter in an abstract inverse estimation model can be based on regularizing the inverse of the operator defining the model. Such regularized-inverse type estimators are constructed with the help of a version of the spectral theorem due to Halmos, after suitable preconditioning. A lower bound to the minimax risk is obtained exploiting the van Trees inequality. The proposed estimators are shown to be asymptotically optimal in the sense that their risk converges to zero, as the sample size tends to infinity, at the same rate as this lower bound. The general theory is applied to deconvolution on locally compact Abelian groups, including both indirect density and indirect regression function estimation.     

利用加权预测的图像迭代盲解卷积

为解决大气湍流造成的图像退化问题,本文鉴于现有的盲解卷积算法收敛性不稳定,计算量大等特点,提出了一种基于加权预测的迭代盲解卷积算法。对目前性能优秀的用迭代实现盲解卷积的L-R算法进行优化,在每次迭代结束后通过加权方法求出预测值,根据预测值计算方向加速算子,从而大大提高算法的收敛速度。实验表明：该算法不仅可对模糊退化图像进行很好的复原,同时与L-R算法相比收敛速度提高约43.8倍,其迭代速度快的特点决定了算法具有较高的工程实用价值。     

盲图像复原研究现状

盲图像复原是在未知或不完全确知相关原始图像与成像点扩展函数的先验知识的情形下,利用所观测到的降质图像对原始图像和点扩展函数进行估计的一种图像处理方法。本文对近年来涌现出的主要盲图像复原算法进行了回顾,并根据相应的理论来源及相互联系将其划分为四大类,对各类复原算法及其改进算法进行了分析和讨论,为更清晰与深刻地认识和理解盲图像复原理论、解决实际图像降质问题提供参考。     

Large Eddy Simulation of Turbulent Reacting Shear Layers Including Finite-Rate Chemistry and Detailed Diffusion Processes

Large eddy simulations (LES) of turbulent temporal shear layers with hydrogen chemistry are performed. In these simulations, approximate deconvolution is applied as an implicit subgrid-scale modeling approach to a reacting flow in combination with a steady flamelet model for the filtered heat release term. No additional heuristical or physical subgrid models are used. The formulation of the flamelet equations in physical space does not only allow to consider a detailed reaction scheme and the extinguished phase but also to take into account detailed diffusion mechanisms (Soret and Dufour effects, multicomponent diffusion coefficients). Two different levels of diffusion approximations are investigated in this work, the aim of which is twofold: Firstly, to verify approximate deconvolution as a tool for convective transport of mass, momentum and energy in gas flow, by comparing the LES results with those of a direct numerical simulation and secondly, to investigate the influence of detailed diffusion on the laminar flamelets and the LES results.     

双原子分子电子能量损失谱的解谱方法

介绍一种双原子分子电子能量损失谱的解谱方法,在利用已知的双原子分子光谱信息及理论计算的Franck-Condon(FC)因子的基础上,通过二次函数调整整个电子态振动强度的轮廓,减少拟合过程中的待定参数个数,降低对FC因子精确性的要求,提高拟合的精度和可信度.用Mathematica语言编写基于以上方法的数据处理程序,改进算法,提高了软件的运行效率.利用该软件处理氢分子的电子能量损失谱,得到氢分子不同电子态的振动跃迁的截面信息,所得结果与以前的实验结果符合很好.     

Fourier自去卷积示波计时电位法的研究

经典的示波计时电位法一般用ｄＥ/ｄｔＥ曲线上的切口深度进行定量测定 .由于施加于电解池的极化电流频率较高 ,使方法灵敏度和分辨率大大降低 .通过选择适当的体系、改进方法等手段可改善示波图的分辨率和提高灵敏度[13],但二者常常不能同时兼备 .Ｆｏｕｒｉｅｒ自去卷积 (ＦＳＤ)是以Ｆｏｕｒｉｅｒ变换为基础、主要用于重叠峰解析的信号处理技术[4 ].它可使信号中峰形变窄、处理后峰的位置不发生变化 .然而 ,由于线性函数和滤噪函数的选择比较困难 ,使其应用受到了限制 .本文探讨了使用小波变换所得模糊项作为线性函数的可能性 ,并将改进…