X射线探测器图像的恢复研究

图像退化是引起X射线探测器图像质量下降的主要原因。图像恢复,可以提高系统的分辨率和对比度灵敏度。通过对射线成像系统图像退化的分析,介绍了反滤波信号恢复方法,并提出了一种近似恢复算法,该算法将反滤波恢复近似为除法运算的恢复。给出了恢复前后的图像及标准差的对比,实验结果表明了该算法的有效性。     

基于多项式外推的Richardson-Lucy算法加速研究

提出一种新的可加速Richardson-Lucy(R-L)图像迭代恢复算法的方法.该方法基于阻尼R-L算法,通过存储阻尼R-L算法的前若干次(n次)迭代运算结果,利用多项式外推法分析这前n次迭代运算结果,并用一个多项式函数近似描述各结果之间的关系.通过该多项式的外推,预测以后的迭代结果,从而减少迭代运算的次数,取得了较好的加速效果.该方法可以实现几乎没有图像失真的复原,并能应用于其他类型的算法.     

激光共焦扫描显微镜中的图像复原方法

在非负值和有限支撑域的递归逆滤波（NAS-RIF）盲图像复原算法的基础上,根据激光共焦扫描显微镜(LCSM)采集到的图像特点,提出了改进方法.首先对LCSM采集到的显微图像进行高斯滤波以提高退化图像的信噪比,然后进行局部直方图均衡以突出显微图像的细节,最后在代价函数中加入空间自适应正则化项,较好地恢复了具有丰富细节信息的显微图像.     

基于改进维纳逆滤波的衍射成像光谱仪数据误差分析与重构

衍射成像光谱仪探测到的高光谱数据需要进行计算与反演才可以得到成像光谱数据,本文对衍射成像光谱仪的成像过程及数据误差产生的原理从空间维和光谱维两方面进行了分析,并针对其光谱重构过程中系统点扩散函数标准差较大时重构结果清晰度较低、存在振铃等问题,提出了基于改进维纳逆滤波的光谱数据重构算法,该方法在分析衍射成像光谱仪数据特点与误差的基础上,将每一次维纳逆滤波的重构结果视为新的模糊图像,利用成像过程及维纳逆滤波的基本原理确定新的模糊图像对应的点扩散函数,反复进行维纳逆滤波达到提高图像清晰度的效果,再根据图像自身的空间和光谱特征分布,进行自适应性的噪声去除.利用模拟的衍射成像光谱数据进行验证,在系统点扩散函数的标准差为2.5的情况下,能得到无振铃的重构结果,且与传统维纳逆滤波法的重构结果进行比较,清晰度、细节能力等指标均有所提高,满足了衍射成像光谱数据应用需求.     

人脸检测中盲解卷积的点传输函数和光学传输函数分析

分析了高速实时人脸检测系统中的光学衍射、离焦和采样效应.通过理论分析,构造了表征光学成像系统空间和频率特性的近似点扩展函数和光学传输函数.在假设这些近似点传输函数已知的基础上,提出了两个盲解卷积滤波器,并且和拉普拉斯算子以及最优聚焦算子的光学传输函数作了对比研究.该系统采用一个马达推动光学镜头来获得高清晰度图像,并在预处理级进行了内插滤波.演示系统在较高的准确率时检测帧率达到15.6fps,实验结果验证了理论分析.     

人脸检测中盲解卷积的点传输函数和光学传输函数分析

分析了高速实时人脸检测系统中的光学衍射、离焦和采样效应.通过理论分析,构造了表征光学成像系统空间和频率特性的近似点扩展函数和光学传输函数.在假设这些近似点传输函数已知的基础上,提出了两个盲解卷积滤波器,并且和拉普拉斯算子以及最优聚焦算子的光学传输函数作了对比研究.该系统采用一个马达推动光学镜头来获得高清晰度图像,并在预处理级进行了内插滤波.演示系统在较高的准确率时检测帧率达到15.6 fps,实验结果验证了理论分析.     

图象消模糊的一种新方法

本文发展了一种非相干光图象消模糊的方法.采用了新的消模糊函数,它比起逆滤波器较易于制作.此函数与模糊图象在空域中进行卷积运算,能得到消模糊图象.在本系统中,可采用扩展单色光源和扩展白光源.由于运用非相干光源,使得在系统中引入了冗余度.因此,与通常的相干光系统相比,这种方法显著地提高了输出图象的信噪比.理论分析证明,此新消模糊函数是逆滤波函数的傅里叶变换.本文给出了实验结果.     

三次相位板波前编码系统彩色图像恢复的迭代算法

采用三次相位板进行景深延拓的波前编码系统得到非对称的点扩展函数.为了获得最终清晰的彩色图像.研究了一种基于广义极小残差法(GMREs)的迭代算法,结合Tikhonov规整化方法,并利用多通道处理过程对中间图像进行左卷积恢复.为了消除恢复图像边界的振铃效应,推导了新的光学成像过程数学模型,该模型采用反镜像边界条件并利用直积近似对卷积核进行处理.模拟数据的分析表明,采用多通道处理过程对彩色图片进行恢复时,新的算法在给出精确的反巷积结果的同时能有效地抑制噪声的放大;实验结果显示,较之经典的维纳滤波恢复结果,新算法能够更好的消除边界的振铃和图像边缘的振动波纹.     

一个小波函数指数参数变化的分岔现象

研究一个高斯小波函数产生的混沌分岔现象.随着小波函数中指数参数的增加，它的分岔图出现了倍周期分岔，然后出现混沌，经过一段混沌区域后又出现2的幂周期.在整个过程中，正分岔与逆分岔完整地结合在一起.改变小波函数的系数出现一些明显的奇数周期，如3周期、5周期等.绘制Lyapunov指数曲线及映射折射过程，对混沌现象进行研究.将小波函数展开成近似的多项式函数，对近似多项式函数的分岔图进行了分析. 关键词： 混沌 分岔 小波函数     

编码孔径成像系统中的点扩散函数

在X光编码孔径成像系统中，系统的点扩散函数决定成像系统的成像质量。由于系统的点扩散函数可用来求解系统的传递函数，并可由此制作实现图像重构的滤波器，因此点扩散函数的精确程度直接影响重构过程中图像的质量。本文以标量衍射理论为基础，从理论上推导出了衍射效应条件下编码孔径中圆环的点扩散函数，并将它用于制作光学系统的滤波器。最后利用Wiener滤波函数对编码重叠像的频谱分布进行滤波处理，再经过逆傅里叶变换得到了重构图像。     

Study of the parameters of a difference image in the presence of a linear phase shift

The spatial filtering in the localization range of the holographic lateral shearing interferograms of a solid object shows that the effect of the subtraction of the compared original data arrays is realized in the presence of a filtering aperture in the center of a dark fringe [1, 2]. Methods for the holographic subtraction of the images involving the detection and spatial filtering in the Fourier plane of the optical system are proposed and realized in [3–5]. Thus, the difference data can be reconstructed with a narrow (unexpanded) laser beam. However, a relatively high level of speckle noise in the difference image is caused by the spatial filtering with a small aperture (laser beam) in the minimum of the superposition field in the Fourier hologram plane. The detection of double-exposed Fourier holograms with a linear phase shift and the effect of the size of the filtering reconstructing beam on the resolution of the difference image are studied. In addition, the application of the multiple exposure for the broadening of the interference maxima is analyzed.     

Effects of k-space filtering and image interpolation on image fidelity in (1)H MRSI.

2D MRSI suffers from the effect of the spatial response function due to the truncation of the sampling of k-space. Filtering of the k-space data-set is often used to suppress the side lobes caused by the effects of the SRF, where the sampled data-set is multiplied with a weighting function before inverse FT. Commonly used filters in MRSI are the cosine, Hanning and Hamming filters. The data-set is often interpolated into a larger image matrix size for analysis, where "Fourier interpolation" (FoI) and "cubic spline interpolation" (CSpI) are two common methods. In this work, the effects of k-space filtering in practical usage was examined, and the image representations of the object for the two interpolation methods were compared.This study showed that application of filtering improves the image representation of the structures in the object and should be used in MRSI. FoI correctly visualizes the information inherent in the data-set, while the features of the object were dependent on the position of the object relative the original matrix in the CSpI interpolated images. FoI should therefore be used for quantitative evaluation of MRSI images.     

核密度估计时-空域滤波红外背景抑制方法

提出一种基于核密度估计的时-空域滤波算法,用于红外搜索跟踪系统图像的背景抑制。算法分为空域滤波和时域滤波两部分。在空域滤波中,采用核密度估计算法对背景进行平滑;在时域滤波中,采用核密度估计算法对经过空域滤波后的图像灰度值进行概率计算,判别属于背景残差的灰度值,然后做进一步的滤除。核方法对背景有很好的光滑性且易于计算机实现,实验表明,这种非参方法设计的时-空域滤波算法对背景杂波有非常良好的抑制效果,信噪比也得到明显提高。     

Look-up table and Gaussian filter-based inverse halftoning method excellent in gray-scale reproducibility of details and flat regions

Halftoning is a technique in which gray-scale images are converted into binary ones, and has been used widely in many practical image processing applications. On the other hand, inverse halftoning is a technique of reproducing a grayscale image from a binary one. One of the sophisticated inverse halftoning methods which can yield a high quality grayscale image is that based on a look-up table (LUT). In this paper, a new inverse halftoning method based on a combination of this LUT method and a Gaussian filter is discussed. Here, the output gray-scale image is reproduced by blending the output of the LUT-based inverse halftoning and that of the Gaussian filtering appropriately in accordance with local statistics of the image. The effectiveness and the validity of the described method are verified through experiments.     

The combined effect of spatial compounding and nonlinear filtering on the speckle reduction in ultrasound images

Recently, a spatial compounding ultrasound imaging method was presented that utilizes a conventional 64-element phased array transducer with two unfocused pistons, each placed at one of the sides of the phased array transducer. This method is augmented here by inclusion of nonlinear filtering of the compounded images. The combined effects of the specific spatial compounding and nonlinear filtering on speckle reduction in the generated ultrasound images are studied and evaluated in two stages: First, the image quality is studied when nonlinear filtering is used as part of the spatial compounding. The study is performed by simulations using the Field II program, by processing several B-mode images of a kidney. The second stage compares the results obtained by the simulations to those obtained by in vitro laboratory experiments. Five different compounding strategies and two nonlinear filters, Gaussian and anisotropic diffusion, are investigated and evaluated in terms of image quality parameters-contrast and signal-to-noise ratio. It is shown that the combination of "averaging+nonlinear Gaussian filtering" produces the greatest improvement of image quality. When compared to a conventional phased array imaging system, the spatial compounding method that includes the conventional 64-element phased array transducer with two unfocused pistons, and employs the "averaging+nonlinear Gaussian filtering" strategy, obtains improvement in SNR that has reached 334%. Thus, though this method necessitates a somewhat wider probe, it produces significantly improved images.     

Development of High Performance Quantum Image Algorithm on Constrained Least Squares Filtering Computation

Recent development of computer technology may lead to the quantum image algorithms becoming a hotspot. Quantum information and computation give some advantages to our quantum image algorithms, which deal with the limited problems that cannot be solved by the original classical image algorithm. Image processing cry out for applications of quantum image. Most works on quantum images are theoretical or sometimes even unpolished, although real-world experiments in quantum computer have begun and are multiplying. However, just as the development of computer technology helped to drive the Technology Revolution, a new quantum image algorithm on constrained least squares filtering computation was proposed from quantum mechanics, quantum information, and extremely powerful computer. A quantum image representation model is introduced to construct an image model, which is then used for image processing. Prior knowledge is employed in order to reconstruct or estimate the point spread function, and a non-degenerate estimate is obtained based on the opposite processing. The fuzzy function against noises is solved using the optimal measure of smoothness. On the constraint condition, determine the minimum criterion function and estimate the original image function. For some motion blurs and some kinds of noise pollutions, such as Gaussian noises, the proposed algorithm is able to yield better recovery results. Additionally, it should be noted that, when there is a noise attack with very low noise intensity, the model based on the constrained least squares filtering can still deliver good recovery results, with strong robustness. Subsequently, discuss the simulation analysis of the complexity of implementing quantum circuits and image filtering, and demonstrate that the algorithm has a good effect on fuzzy recovery, when the noise density is small.     

Spatial high-pass filtering of images using the photochemical adjacency effect

A very practical method for spatial high-pass filtering of images, which can be carried out in any normally equipped darkroom, is based on the artificially enhanced adjacency. It is shown that a quasi-MTF can be defined, representing a convenient tool for selecting the most useful film-developer combination for a given high-pass filtering task. Results of MTF-measurements on commercially available materials and of filtering experiments are presented.     

Twin-image problem in digital holography—a survey(Invited Paper)

Zero-order and twin images are a serious obstacle in achieving a high-quality output in in-line digital holography （DH）. They decrease the useful bandwidth of the off-axis DH. Over the years the twin image removal problem was approached both by instrumental and numerical means. The paper provides an extended survey of the proposed solutions with their pros and cons as a guide for further advance in this field. Processing of a single spatial carrier fringe pattern involves spatial filtering in the frequency domain, spatial phase-shifting （PS） or wavelet transform. A point source digital holographic microscopy （DHM）, introduction of calibration measurements or various modifications of PS technique are instrumental solutions to the twin image problem for in-line DH. Numerical solutions to the same problem include iterative and non-iterative approaches, diffraction-based and inverse problem solutions, reconstruction of purely real or phase objects and of complex objects, reconstruction of plane and volume objects. Elimination only of the zero-order image relies on non-linear filtering or additional calibration measurements.     

可调节自适应遥感影像融合方法研究

大部分常用的遥感影像融合方法都存在一个缺陷:只能产生一个特定的融合结果,用户无法控制最终的结果应该保留多少光谱信息或细节信息。提出了一种基于小波变换的可调节自适应遥感影像融合方法,该方法首先分别将待融合影像进行小波分解,然后,通过引入2个可调节参量,在小波域内融合,最后通过小波逆变换得到融合结果。使用法国地球资源探测卫星(SPOT)图像和陆地资源卫星专题绘图仪(landsat TM)图像,将该方法与传统的小波变换融合法、强度色散饱和变换融合法和主成分变换法进行对比试验,结果表明,该方法可以在细节保留和光谱保持两方面达到不同程度的平衡,在合理的参量组合下,融合图像的目视效果和统计指标优于传统融合方法。