High quality non-blind image deconvolution using the Fields of Experts prior

In this paper, we propose a non-blind image deconvolution method under Bayesian probabilistic framework. A robust prior, i.e., the Fields of Experts (FoE) prior which is learned from natural images is adopted to regularize the latent image. To solve the resulted optimization problem, the Split Bregman algorithm is utilized. We use a data set to verify the effectiveness of the proposed approach. Experimental results show that the restored images are of higher quality than that of some state of the art algorithms.     

Motion deblurring using edge map with blurred/noisy image pairs

Motion deblurring methods using blurred/noisy image pairs usually include denoising process of the noisy image. Because both remaining noise and distorted fine details in the denoised image cause an error on deblurring, we propose an algorithm using an edge map of the noisy image to retain sharp edge information while neglecting noise in any smooth region that does not contain information about the motion that occurred during the exposure. In addition, the blur kernel is efficiently estimated by employing the fast total variation regularization method for the gradients of blurred and noisy images only on edge regions. For latent image restoration, another fidelity term is added, which compares the gradients of the noisy and estimated latent images on edge regions to preserve the fine details of the noisy image. To model a sparse distribution of real-world image gradients, a deconvolution method imposing hyper-Laplacian priors based on an alternating minimization scheme is also derived to restore a latent image efficiently. Experimental results show that the peak signal-to-noise ratios of the restored images against the original latent images have been increased by 11.1% on average, when compared to the existing algorithms using an image pair.     

An image deblurring method using diffraction gratings

A method of image deblurring is described, in which the restoration filter is derived from Ronchi rulings. Although two-dimensional spatial filtering is used, the method employs a line source, resulting in significant noise reduction. Experimental results are given.     

An improved image deconvolution approach using local constraint

Conventional deblurring approaches such as the Richardson–Lucy (RL) algorithm will introduce strong noise and ringing artifacts, though the point spread function (PSF) is known. Since it is difficult to estimate an accurate PSF in real imaging system, the results of those algorithms will be worse. A spatial weight matrix (SWM) is adopted as local constraint, which is incorporated into image statistical prior to improve the RL approach. Experiments show that our approach can make a good balance between preserving image details and suppressing ringing artifacts and noise.     

An improved computing method for the image edge detection

The framework of detecting the image edge based on the sub-pixel multi-fractal measure (SPMM) is presented. The measure is defined, which gives the sub-pixel local distribution of the image gradient. The more precise singularity exponent of every pixel can be obtained by performing the SPMM analysis on the image. Using the singularity exponents and the multi-fractal spectrum of the image, the image can be segmented into a series of sets with different singularity exponents, thus the image edge can be detected automatically and easily. The simulation results show that the SPMM has higher quality factor in the image edge detection.     

An improved deconvolution method for X-ray coded imaging in inertial confinement fusion

In inertial confinement fusion （ICF）, X-ray coded imaging is considered as the most potential means to diagnose the compressed core. The traditional Richardson-Lucy （RL） method has a strong ability to deblur the image where the noise follows the Poisson distribution. However, it always suffers from over-fitting and noise amplification, especially when the signal-to-noise ratio of image is relatively low. In this paper, we propose an improved deconvolution method for X-ray coded imaging. We model the image data as a set of independent Gaussian distributions and derive the iterative solution with a maximum-likelihood scheme. The experimental results on X-ray coded imaging data demonstrate that this method is superior to the RL method in terms of anti-overfitting and noise suppression.     

Spectral restoration using semi-blind deconvolution method with detail-preserving regularization

Peak-details are often smoothed when deconvolution methods are used for spectral restoration. In order to preserve spectral details, detail-preserving regularization is devised and a semi-blind deconvolution method with the detail-preserving regularization (SBD-DP) is proposed. The cost function of SBD-DP is formulated and the numerical solution processes are deduced for restoring spectra and estimating parameter of blur kernel. The deconvolution results of simulated spectra demonstrate that the proposed SBD-DP can restore the spectrum effectively and has a merit on preserving peak details, as well as can estimate the parameter of blur kernel accurately. Then the deconvolution result of experimental Raman spectrum indicates the effectiveness of the proposed SBD-DP method on improving spectral resolution.     

Measurement of edge residual stresses in glass by the phase-shifting method

Control and measurement of residual stress in glass is of great importance in the industrial field. Since glass is a birefringent material, the residual stress analysis is based mainly on the photoelastic method. This paper considers two methods of automated analysis of membrane residual stress in glass sheets, based on the phase-shifting concept in monochromatic light. In particular these methods are the automated versions of goniometric compensation methods of Tardy and Sénarmont. The proposed methods can effectively replace manual methods of compensation (goniometric compensation of Tardy and Sénarmont, Babinet and Babinet-Soleil compensators) provided by current standards on the analysis of residual stresses in glasses.     

Development of an improved energy-based method for residual stress assessment

In this study, an improved energy-based method is proposed to measure the equi-biaxial residual stress of bulk materials using spherical indentation. Through analysis of the load–depth curve and residual indentation profile, two calculation methods of the energy of residual stress are proposed, one of which is determined from the load–depth curve and the other based on the Hertizan theory. Finite element analysis was used to establish their relationship, which is the function of the residual stress and material parameters. According to reverse analysis, the proposed method can be used to quickly and effectively determine residual stress. To verify the model, indentation experiments were performed using a ZHU0.2/Z2.5 testing machine. A comparison with conventional X-ray diffraction results showed that the improved method is suitable for the quantitative assessment of residual stress in industrial facilities.     

An effective method of direct QSD extraction using combined partial deconvolution

We demonstrate the use and robustness of a new quadrupole splitting distribution extraction method that gives unique arbitrary shapeP(t) curves and is not sensitive to the elemental doublet parameters or to practical details such as chosen velocity and splitting ranges. It is applied to the real⁵⁷Fe Mössbauer spectrum of an Fe₃₊-chlorite produced by oxidation.On leave from: Department of Materials Physics, University of Science and Technology Beijing, Beijing 100083, PR China.     

Holographic method of deconvolution and analytic continuation

In this paper a method of analytic continuation for gaining spatial frequency components of an object filtered by an optical system, based on the Taylor series and the series of orthogonal polynomials, is proposed in connection with the holographic method of deconvolution. An analysis of the efficiency of this method is carried out in terms of information theory and improving terms are explicitly calculated. Some simple realizations of the present theory are also proposed. Higher frequency components of the object reconstructed with the help of this method will permit to observe greater details of the restored object.This work was partly done during a stay of the author at the University of Florence.The author thanks Profs G. W. Stroke, G. Toraldo di Francia and B. Havelka for interesting discussions and fruitful comments. A financial support of Ministero degli Affari Esteri in Rome during the stay of the author at the University of Florence is acknowledged, too.     

高能闪光照相中Sobel算子的边缘检测方法

针对高能闪光照相中投影图像的特点,对数字图像处理中具有代表性的Sobel边缘检测算法进行了分析,发现该算法存在检测出的边缘粗和人为进行阈值的选取会造成边缘点的误判的缺点;为此提出了一种阈值确定方法和基于最大梯度的定位准则算法。改进的算法实测结果表明：该方法有效地解决了Sobel算子检测出的边缘过粗的问题,得到的边缘较细,定位精确,提高了边缘检测精度,可用于高能辐射照相中的边缘提取。     

Color image edge detection method using VTV denoising and color difference

The traditional Canny edge uses Gaussian filter to suppress the noise, it also smoothes out the image edges. An improved Canny edge detection method for color image is proposed in this paper, the improved method uses fast vectorial total variation (VTV) minimization model to remove noise in color image, and then calculates the color difference and direction in CIELAB color space, which is used for non-maximal suppression. Finally, the improved method extracts the edges by the double-threshold method. The experimental results show that the proposed method achieves better performance than the traditional Canny edge detector. It can remove noise while preserving the image edges, and effectively detect the image edges.     

A method of improving overall resolution in ultrasonic array imaging using spatio-temporal deconvolution

In this paper a beamforming method for ultrasonic array imaging is presented that performs both spatial and temporal deconvolution based on a minimum mean square error (MMSE) criteria. The presented MMSE receive mode beamformer performs a regularized inversion of the propagation operator for the ultrasonic array system at hand. The MMSE beamformer accounts for the transmit and receive processes, defined in terms of finite array element sizes, transmit focusing laws and electrical transducer characteristics. The MMSE beamformer is compared to the traditional delay-and-sum (DAS) beamformer with respect to both resolution and signal-to-noise ratio. The two algorithms are compared using both simulated and measured data. The simulated data was obtained using ultrasonic field simulations and the measured data was acquired using a linear phased array imaging wire targets in water. The results show that the MMSE beamformer has superior temporal and lateral resolution compared to DAS. It is also shown that the MMSE beamformer can be expressed as a filter bank, which enables parallel processing at high frame rates.     

Prediction of reverberation time using the residual minimization method

In many practical situations the assumption of sound field dispersion needed for the application of the Sabine’s theory is not fulfilled. In general, sound field is sufficiently dispersed if there are no large differences in the dimensions of the room, limiting partitions are not parallel, or the sound absorbing material is uniformly distributed. In practice, very few of these requirements are satisfied. As a result, a number of other formulas describing reverberation time have been created, for example Fitzroy’s or Neubauer’s formulas. However, these methods in many cases differ significantly from the actual measurements. The paper presents a method used to estimate reverberation time as well as its applicability potential involving laboratory models and auditorium rooms. The proposed method can be classified into a group of learning methods and involves the use of statistical methods which allow for approximation with the use of the least squares method.     

利用金属掩模法制备钉扎型磁性隧道结

利用金属掩模法和Ir22Mn78合金反铁磁钉扎层，制备了四种钉扎型的Py/Al2O3/Py，Py/Al2O3/Co，Co/Al2O3/Py和Co/Al2O3/Co磁性隧道结，坡莫合金的成分为Py＝Ni79Fe21.例如：利用狭缝宽度为100?μm的金属掩模，直接制备出室温隧穿磁电阻比值为17.2%的磁性隧道结Co/Al2O3/Co，其结电阻为76Ω,结电阻和结面积的积矢为76×10_{4Ωμm2，自由层的偏转场为1114?A/m，并且在外加磁场0.1114A·m-1之间时室温磁电阻比值 关键词： 磁性隧道结 隧穿磁电阻 磁随机存储器 金属掩模}     

Blind image deconvolution using sparse and redundant representation

This work devotes to the image deconvolution problem that restores clear image from its blurred and noisy measurements with little prior about the blur. A deconvolution method based on sparse and redundant representation theory is developed in this paper. It firstly represents the blur and image over different redundant dictionaries and imposes sparsity constraint to their representation coefficients respectively, then alternately estimates them using an iterative algorithm employing optimization technique. Experimental results on astronomical images show that the proposed method can achieve as good performance as the method requiring a known blur, which demonstrates its effectiveness.     

A recursive color image edge detection method using Green's function approach

In this paper, an extended version of image edge detector using Green's function approach is proposed for detection of edges in the color vector space field. In the proposed method, the relationship between the Red, Green and Blue components is considered to design a differential operator for detection of edges in color images. By using the proposed operator, partial derivatives of all components of color image can simultaneously affect on the edge detection process. Therefore the proposed method can preserve the vector nature of color images during the edge processing stages. Also, the proposed method is compared both quantitatively and qualitatively with other color edge detectors. Experimental results show that the proposed method can efficiently preserve the edges even when the color images corrupted with different levels of noise.     

A quality control method for detecting and suppressing uncorrected residual motion in fMRI studies

Motion correction is an important step in the functional magnetic resonance imaging (fMRI) analysis pipeline. While many studies simply exclude subjects who are estimated to have moved beyond an arbitrary threshold, there exists no objective method for determining an appropriate threshold. Furthermore, any criterion based only upon motion estimation ignores the potential for proper realignment. The method proposed here uses unsupervised learning (specifically k-means clustering) on features derived from the mean square derivative (MSD) of the signal before and after realignment to identify problem data. These classifications are refined through analysis of correlation between subject activation maps and the mean activation map, as well as the relationship between tasking and motion as measured through regression of the canonical hemodynamic response functions to fit both estimated motion parameters and MSD. The MSD is further used to identify specific scans containing residual motion, data which is suppressed by adding nuisance regressors to the general linear model; this statistical suppression is performed for identified problem subjects, but has potential for use over all subjects. For problem subjects, our results show increased hemodynamic activity more consistent with group results; that is, the addition of nuisance regressors resulted in a doubling of the correlation between the activation map for the problem subjects and the activation map for all subjects. The proposed method should be useful in helping fMRI researchers make more efficient use of their data by reducing the need to exclude entire subjects from studies and thus collect new data to replace excluded subjects.     

一种改进的数字散斑相关方法用于检测人的口型变化

提出了一种基于数字散斑相关测量技术的口型变化检测技术,该技术以白光数字散斑相关测量方法为基础,根据实际应用的需要,引入重心算法并进行了改进,可以实时地检测人说话时的口型变化。通过实验表明,提出的方法是一种实用的、快速、高精度的口型变化测试方法,可为今后的唇语识别技术奠定基础。