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1.
A tomographic reconstruction method based on Monte Carlo random searching guided by the information contained in the projections
of radiographed objects is presented. In order to solve the optimization problem, a multiscale algorithm is proposed to reduce
computation. The reconstruction is performed in a coarse-to-fine multigrid scale that initializes each resolution level with
the reconstruction of the previous coarser level, which substantially improves the performance. The method was applied to
a real case reconstructing the internal structure of a small metallic object with internal components, showing excellent results. 相似文献
2.
本文提出从高分辨电子显微像中,利用光学、全息和部分相干等方法,提取传递函数,制作相位和振幅滤波器,实现解卷,提高高分辨电子显微像的分辨率. 相似文献
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In the direct simulation Monte‐Carlo (DSMC) method for simulating rarefied gas flows, the velocities of simulator particles that cross a simulation boundary and enter the simulation space are typically generated using the acceptance–rejection procedure that samples the velocities from a truncated theoretical velocity distribution that excludes low and high velocities. This paper analyses an alternative technique, where the velocities of entering particles are obtained by extending the simulation procedures to a region adjacent to the simulation space, and considering the movement of particles generated within that region during the simulation time step. The alternative method may be considered as a form of acceptance–rejection procedure, and permits the generation of all possible velocities, although the population of high velocities is depleted with respect to the theoretical distribution. Nevertheless, this is an improvement over the standard acceptance–rejection method. Previous implementations of the alternative method gave a number flux lower than the theoretical number required. Two methods for obtaining the correct number flux are presented. For upstream boundaries in high‐speed flows, the alternative method is more computationally efficient than the acceptance–rejection method. However, for downstream boundaries, the alternative method is extremely inefficient. The alternative method, with the correct theoretical number flux, should therefore be used in DSMC computations in favour of the acceptance–rejection method for upstream boundaries in high‐speed flows. Copyright © 2003 John Wiley & Sons, Ltd. 相似文献
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在分析红外图象和视图象差异的基础上,研究了一种适用于可视图像序列的运动小目标检测算法。受目标影响的象素点具有较弱的时间相关性,即相对普通象素点有较大的时间方差,根据此特征,用管道更新的方法产生新方差图象序列,再用管道更新的方法累积,增加信噪比,然后用基于统计均值的自适应门限方法分割出目标,最后将原图象的梯度倒数作为象素点强度的加权,有效地抑制灰度突变边界的传感器噪音,保存目标点。 相似文献
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Digital image processing techniques have been applied to the analysis of cellular smoked foil patterns from gaseous detonations. In particular, the two-dimensional autocorrelation function is applied to digital cell pattern images and an orientational correlation parameter is calculated. Taking line profiles along the directions of highest correlation provides an unbiased method of determining the mean cell size in each of the two principal directions. By analyzing the width, amplitude and angular position of the orientational correlation plots, information can be extracted concerning the cellular pattern regularity, the relative angular correlation between two sets of transverse waves in two directions, and the mean shape or elongation of the cells within the pattern. The technique is applied to smoked foils from oxyacetylene mixtures with argon dilutions ranging from 0 to 75% to quantify the increase in regularity with argon dilution. This method provides a simple and useful way of analyzing cellular patterns and constitutes a promising technique for improving smoked foil diagnostics. 相似文献
10.
Dirk P. Kroese Sergey Porotsky Reuven Y. Rubinstein 《Methodology and Computing in Applied Probability》2006,8(3):383-407
In recent years, the cross-entropy method has been successfully applied to a wide range of discrete optimization tasks. In
this paper we consider the cross-entropy method in the context of continuous optimization. We demonstrate the effectiveness
of the cross-entropy method for solving difficult continuous multi-extremal optimization problems, including those with non-linear
constraints.
相似文献