自由基聚合型光致聚合物中全息图像质量的动态特性研究

用实验方法研究了光致聚合物中全息存储再现图像质量的动态特性,以信噪比损失作为图像质量变化的衡量指标,进行了暗增长和均匀后曝光过程监测图像实验。实验结果表明,在暗增长和均匀后曝光过程中,再现图像强度和质量经历先增长后下降的动态过程。以噪声光栅的形成和发展对实验结果进行了初步的解释。以信噪比损失不大于3 dB为判据考察了全息图对暗反应和均匀后曝光过程的宽容程度,对于不同的记录条件确定了暗反应和均匀后曝光过程的特征时间。在特征时间内,再现图像的质量和强度都是可以接受的。在复用记录时,为保证所有全息图有均衡的衍射效率和良好的图像质量,必须考虑再现图像质量和强度的动态变化因素。     

The adaptive sinogram restoration algorithm based on anisotropic diffusion by energy minimization for low-dose X-ray CT

Apparent streak artifacts will present in reconstructed images due to excessive quantum noise in low-dose X-ray imaging process. Estimating a noise-free sinogram to satisfy the filtered back-projection (FBP) reconstruction is an effective way to solve this problem. In this paper, we propose a novel sinogram noise reduction method by energy minimization. An adaptive smoothness parameter based on a modified anisotropic diffusion coefficient is applied for an optimal estimation. The smoothness parameter can make the method effectively adjust the degree of smoothness according to the noise level and the region feature in the sinogram. Visual effect together with quantitative analysis of the experimental result shows the developed approach has the excellent performance in protection of the edge and removal of streak artifacts in the reconstructed image.     

Reconstruction method of computational ghost imaging based on non-local generalized total variation北大核心CSCD

鬼成像是一种能够透过大雾等恶劣环境的成像技术。针对传统鬼成像重建图像存在噪声较多、图像对比度较低等问题,将非局部广义全变分方法用于鬼成像的图像重建之中,提出基于非局部广义全变分的计算鬼成像重建方法。所提方法构造了一种非局部相关性权重设计梯度算子,将其代入全变分重建算法中,使得重建的图像能有效去除噪声的同时实现细节较好的还原。首先在不同条件下进行仿真模拟,得到所提方法的峰值信噪比相对其他方法提升1 dB左右,且具有更好的主观视觉效果,进而设计并搭建实验平台对算法的有效性进行验证,实验结果证明了所提方法在去除噪声和细节重建等方面的优越性。     

Noise reduction for low-dose X-ray CT based on fuzzy logical in stationary wavelet domain

Apparent streak-like artifacts will present in reconstructed images due to excessive quantum noise in low-dose X-ray imaging process. Dealing with the noisy sinogram before a filtered back-projection (FBP) is a useful solution to solve this noise problem. In this paper, we proposed a novel noise restoration method combining wavelet and fuzzy logical technology for low-dose computed tomography (CT) sinogram. The method first utilizes stationary wavelet transform on the noisy sinogram, namely decomposes the sinogram to different resolution levels. And then, at each decomposed resolution level, a fuzzy shrinkage filter is applied to restore the noise-contaminated wavelet coefficients. Simulations were performed and indicated that the proposed method could significantly suppress noise and reduced streak-like artifacts in reconstructed images while at the same time maintaining the image sharpness.     

A statistical iteration approach with energy minimization to sinogram noise reduction for low-dose X-ray CT

Low-dose CT imaging has been particularly used in modern medical practice for its advantage on reducing the radiation dose to patients. However, excessive quantum noise is present in low dose X-ray imaging along with the decrease of the radiation dose; thus, there are obvious streak-like artifacts in reconstructed images. The statistical iterative reconstruction approach applied to the noisy sinogram before a filtered back-projection (FBP) is a resolution to deal with the noisy problem. In this paper, the statistical property of the noise sinogram was considered to achieve a satisfactory image reconstruction and a statistical iterative method with energy minimization was proposed to address the problem of streak-like artifacts. Simulations were performed and indicated that the proposed method could suppress noise and obviously decrease streak-like artifacts in reconstructed images.     

基于lp范数的压缩感知图像重建算法研究

图像重建是光学成像、光声成像、声纳成像、核磁共振成像、 天体成像等物理成像领域中的关键技术之一. 近年来提出的压缩感知理论指出: 对稀疏或者可压缩信号进行少量非自适应线性投影,投影信号含有足够的信息, 从而能对信号进行高概率重建. 压缩感知已被应用于多种物理成像系统. 将罚函数法和修正Hesse阵序列二次规划方法相结合, 并采用了分块压缩感知思想, 提出一种基于l_p范数的压缩感知图像重建算法. 以cameraman, barbara和mandrill图像为例, 采用该算法进行图像重建. 首先, 在不同采样率下对图像重建. 即便采样率低至0.3时, 也能获得高达32.23dB的信噪比, 重建图像清晰可辨. 验证了该算法的正确性. 其次, 将该算法与正交匹配追踪算法进行对比, 在采样率达到0.5以上时, 能够获得高信噪比的重建图像, 成像时间也大为减少, 特别是采样率为0.7时, 成像时间减少88%. 最后, 与现有基于l_p 范数的压缩感知图像重建算法进行对比, 计算结果表明在成像质量有所提高的基础上, 成像时间大为缩短. 关键词： 图像重建 压缩感知 罚函数 修正Hesse阵序列二次规划     

Methods of spectral estimation in local nuclear quadrupole resonance with a dispersion

The spectral estimation in local nuclear quadrupole resonance at a high noise level is performed for the first time using the modern techniques of linear prediction (LPSVD) and matrix pencil (ITMPM). The fast Fourier transform with signal accumulation does not ensure the required sensitivity in the case of weak signals when the object and the receiver of the spectrometer are spaced widely apart or when there is an effect of adverse factors (screening, interference, random disturbance, etc.), which is typical of remote monitoring in actual practice. It is demonstrated that the use of the proposed techniques considerably increases the efficiency of spectral estimation in this field of solid-state spectroscopy and, in particular, avoids the phase errors arising in usual experiments at a signal-to-noise ratio of less than 0.5.     

Enhanced resolution for EPR imaging by two-step deblurring

The broad spectrum of spin probes used for electron paramagnetic resonance imaging (EPRI) result in poor spatial resolution of the reconstructed images. Conventional deconvolution procedures can enhance the resolution to some extent but obtaining high resolution EPR images is still a challenge. In this work, we have implemented and analyzed the performance of a postacquisition deblurring technique to enhance the spatial resolution of the EPR images. The technique consists of two steps; noniterative deconvolution followed by iterative deconvolution of the acquired projections which are then projected back using filtered backprojection (FBP) to reconstruct a high resolution image. Further, we have proposed an analogous technique for iterative reconstruction algorithms such as multiplicative simultaneous iterative reconstruction technique (MSIRT) which can be a method of choice for many applications. The performance of the suggested deblurring approach is evaluated using computer simulations and EPRI experiments. Results suggest that the proposed procedure is superior to the standard FBP and standard iterative reconstruction algorithms in terms of mean-square-error (MSE), spatial resolution, and visual judgment. Although the procedure is described for 2D imaging, it can be readily extended to 3D imaging.     

On the possibility of using the maximum entropy method in ultrasonic nondestructive testing for scatterer visualization from a set of echo signals

We have studied the possibility of solving the inverse scattering problem in the Born approximation, i.e., the reconstruction of scatterer images from the measured set of echo signals. We have considered generalization of the classical combined SAFT (C-SAFT) algorithm to the case of multiple reflections from uneven boundaries of the tested object taking into account the transformation of the wave type for several positions of the antenna grid, which makes it possible to obtain high-quality scatterer images. Representation of the direct problem in matrix form makes it possible to switch to solving the inverse problem, which can be solved using the Tikhonov regularization procedure, because it is an ill-posed. We have considered the possibility of using the entropy of the image estimate as the stabilizing functional that forms the essence of the maximum entropy method (MEM). The advantage of the MEM over the conventionally used linear C-SAFT method has been shown. The ray model taking into account reflections of rays from the boundaries of the tested object with uneven boundaries has been used for constructing the function estimate. We have demonstrated the ability of the MEM to obtain the scatterer images with superresolution and to suppress the “side lobes” of the function of the point scattering on the collapsed set of echo signals. The use of echo signals reflected from the boundaries of the tested object makes it possible to reconstruct the scatterer shape more exactly. Examples of images reconstructed by the MEM on echo signals obtained in the numerical and model experiments have been presented.     

多通道相位图像的改进型自适应重建算法

自适应重建(Adaptive Reconstruction,AR)算法被广泛应用于磁共振图像的多通道合并问题上.AR算法不需要直接采集各个线圈的灵敏度信息,而是通过通道间信号及噪声相关矩阵,估算出各个通道的灵敏度,从而保证了合并的幅值图像具有较高的信噪比(Signal-to-Noise Ratio,SNR).然而,由于AR算法没有针对相位图像的合并问题进行优化,导致重建出的相位图像具有不确定性.另外,受各通道之间相位偏移及低信噪比相位图像的影响,重建结果可能包含伪影.该文提出了一种改进型AR算法,估算并移除了各通道之间的相位偏移,同时对多通道数据的相位进行质量评估及通道重排,用以进行后续自适应重建.仿体及在体实验表明,该方法可以有效提升AR算法稳定性、消除重建图像中存在的伪影,同时保持合并后幅值图像及相位图像的高信噪比.     

基于多角度无透镜傅里叶变换数字全息的散斑噪声抑制成像研究

在数字全息成像中,散斑噪声严重影响了再现像的信噪比和成像分辨率,因此为了提高数字全息成像质量,迫切需要抑制再现像的散斑噪声.分析并给出了矩形散射光斑的强度协方差,定量计算了特定实验条件下产生退相关散斑图样的最小角度差.结合透镜的性质设计并搭建了多角度无透镜傅里叶变换数字全息成像系统,利用光纤端面在透镜焦平面的二维机械移动代替传统反射镜的旋转,使照明光束在不改变照明位置和大小的同时,可任意改变光束方向.移动光纤端面使多角度照明满足最小角度差,获取了81幅数字全息图.利用单次快速傅里叶逆变换实现数值再现,对多幅再现像的强度像求平均,实验结果表明散斑对比度降低为单幅再现像的14.6%,使图像信噪比提高了6.9倍.该抑制散斑的多角度数字全息成像方法有效的抑制了散斑噪声,且成像光路结构简单,可操作性强.     

An improved POCS super-resolution infrared image reconstruction algorithm based on visual mechanism

The traditional projection onto convex sets (POCS) super-resolution (SR) reconstruction algorithm can only get reconstructed images with poor contrast, low signal-to-noise ratio and blurring edges. In order to solve the above disadvantages, an improved POCS SR infrared image reconstruction algorithm based on visual mechanism is proposed, which introduces data consistency constraint with variable correction thresholds to highlight the target edges and filter out background noises; further, the algorithm introduces contrast constraint considering the resolving ability of human eyes into the traditional algorithm, enhancing the contrast of the image reconstructed adaptively. The experimental results show that the improved POCS algorithm can acquire high quality infrared images whose contrast, average gradient and peak signal to noise ratio are improved many times compared with traditional algorithm.     

An Acceleration Algorithm for Image Reconstruction Based on Continuous-Discrete Mapping Model

In image reconstruction for X-ray computed tomography, images reconstructed by filtered backprojection (FBP) include systematic errors because the FBP method does not take into account some of the properties of the actual imaging system such as the divergence of X-ray beam. One solution to this problem is to use algebraic reconstruction methods, such as generalized analytic reconstruction from discrete samples and natural pixel decomposition. However, in the process of reconstruction using these methods, it is necessary to solve the linear algebraic equations which have a large coefficient matrix. In this paper, we propose a method to accelerate the iteration solving these equations by preconditioning the coefficient matrix using a polynomial function. The results of the computer simulations show the effectiveness of the proposed method.     

Improvement of signal-to-noise ratio in digital holography using wavelet transform

The basic problem in optical and digital holography is the presence of speckle noise in the reconstruction process, which reduces the signal-to-noise ratio (SNR). The presence of speckle noise is serious drawback in optical and digital holography since it substantially reduces the SNR in the reconstructed image. In this paper, we present wavelet filtering to improve SNR in the reconstructed images from digital holograms. Experimental results are presented.     

Improvement of speckle noise suppression in digital holography by rotating linear polarization state

An improved polarization recording approach to reduce speckle noise in digital holography is proposed. Multiple off-axis holograms are obtained by rotating the linear polarization state of both illumination and reference wave simultaneously. By averaging the intensity fields, the speckle noise in the reconstructed images is well suppressed. Statistical evaluation of the experimental results shows the effectiveness and improvement of the proposed method.     

A practical and flexible implementation of 3D MRI in the Earth's magnetic field

The Earth's magnetic field, though weak, is appealing for NMR applications because it is highly homogeneous, globally available and free. However, the practicality of Earth's field NMR (EFNMR) has long been limited by the need to perform experiments in outdoor locations where the local field homogeneity is not disrupted by ferrous or magnetic objects and where ultra-low frequency (ULF) noise sources are at a minimum. Herein we present a flexible and practical implementation of MRI in the Earth's magnetic field that demonstrates that EFNMR is not as difficult as it was previously thought to be. In this implementation, pre-polarization and ULF noise shielding, achieved using a crude electromagnet, are used to significantly improve signal-to-noise ratio (SNR) even in relatively noisy environments. A three axis gradient coil set, in addition to providing imaging gradients, is used to provide first-order shims such that sub-hertz linewidths can routinely be achieved, even in locations of significant local field inhomogeneity such as indoor scientific laboratories. Temporal fluctuations in the magnitude of the Earth's magnetic field are measured and a regime found within which these variations in Larmor frequency produce no observable artefacts in reconstructed images.     

Methods of filtering densities reconstructed from line projections

We present details important for practical applications of a new algorithm for filtering densities reconstructed from their line projections. The method is applied to densities reconstructed via the Cormack method from both model projections and 2D angular correlation of positron annihilation radiation spectra in CeIn₃ and ErGa₃. It is shown that this algorithm filters the experimental noise as well as enhances some details of the reconstructed densities, which then reveals their fine features. We also compare this way of filtering with the effects of imposing symmetry conditions on densities reconstructed for cubic systems. PACS 78.70.Bj; 87.59.Fm; 74.25.Jb     

Speckle noise reduction by the composition of diffused Fraunhofer holograms

The image reconstructed from a composite hologram is compared with that obtained by multiple-exposure of images independently reconstructed from a single element and also with that from a synthetic-aperture hologram. The experimental results show the difference in the principle of speckle noise reduction with these three methods and prove that the composite hologram arranged only in a row is sufficient for reducing the speckle noise.     

Quantitative assessment of lateral resolution improvement in digital holography

Controllable experimental features such as wavelength, camera’s specifications and reconstruction distance, determine the theoretical limit for lateral resolution in digital holography; however, due to the speckle noise associated to any coherent imaging system it is not possible to reach this theoretical limit. In this paper, a quantitative study the lateral resolution for digital holography under the effect the speckle noise is carried out. It is shown that by reducing the contrast of the speckle noise the resolution capabilities of digital holography are improved; the signal-to-noise ratio of the reconstructed holograms is the metric use to quantitatively assess the reached resolution in the holographic experiments.     

In situ investigation on rapid microstructure evolution in extreme complex environment by developing a new AFBP-TVM sparse tomography algorithm from original CS-XPCMT

A new sparse tomography method for observing the rapid internal microstructure evolution of material, called the Algebraic Filtered-Back-Projection and Total Variation Minimization (AFBP-TVM) iteration sparse reconstruction algorithm, was proposed in this paper. The new algorithm was developed by combining the two techniques of the Algebraic Reconstruction Technique (ART) and the Filtered-Back-Projection (FBP) on the basis of analysis in linear space. A series of numerical reconstruction experiments were conducted to validate the new algorithm. The results indicated the new algorithm can obtain satisfactory reconstruction images from 1/6 of the projections that were used in traditional algorithms. So the time spent on projection acquisition process can be reduced to 1/6 of that in traditional tomography method. The quality of images reconstructed by new algorithm was better than other algorithms, which was evaluated by three quantitative parameters. The normalized average absolute distance criterion and the normalized mean square criterion, which were used to evaluate the relative error of the reconstruction results (smaller value means better quality of reconstruction), decreased from 0.3758 to 0.1272 and from 0.1832 to 0.0894 respectively. The standardized covariance criterion, which was used to evaluate the similarity level (greater value means higher accuracy of reconstruction), increased from 92.72% to 99.30%. Finally, the new algorithm was validated under actual experimental conditions. The results indicated that the AFBP-TVM algorithm obtained better reconstruction quality than other algorithms. It meant that the AFBP-TVM algorithm may be a suitable method for in situ investigation on material's rapid internal microstructure evolution in extreme complex environment.