Compression and reconstruction of MRI images using 2D DCT.

In magnetic resonance imaging (MRI), the original data are sampled in the spatial frequency domain. The sampled data thus constitute a set of discrete Fourier transform (DFT) coefficients. The image is usually reconstructed by taking inverse DFT. The image data may then be compressed using the discrete cosine transform (DCT). We present here a method of treating the data that combines two procedures, image reconstruction and data compression. This method may be particularly useful in medical picture archiving and communication systems (PACS) where both image reconstruction and compression are important issues.     

Double image encryption based on discrete multiple-parameter fractional Fourier transform and chaotic maps

A double image encryption method is proposed by utilizing discrete multiple-parameter fractional Fourier transform and chaotic maps. One of the two original images scrambled by one chaotic map is encoded into the amplitude of a complex signal with the other original image as its phase. The complex signal multiplied by another chaotic random phase mask is then encrypted by discrete multiple-parameter fractional Fourier transform. The parameters in chaotic map and discrete multiple-parameter fractional Fourier transform serve as the keys of this encryption scheme. Numerical simulations have been done to demonstrate the performance of this algorithm.     

An unsupervised deep learning technique for susceptibility artifact correction in reversed phase-encoding EPI images

Echo planar imaging (EPI) is a fast and non-invasive magnetic resonance imaging technique that supports data acquisition at high spatial and temporal resolutions. However, susceptibility artifacts, which cause the misalignment to the underlying structural image, are unavoidable distortions in EPI. Traditional susceptibility artifact correction (SAC) methods estimate the displacement field by optimizing an objective function that involves one or more pairs of reversed phase-encoding (PE) images. The estimated displacement field is then used to unwarp the distorted images and produce the corrected images. Since this conventional approach is time-consuming, we propose an end-to-end deep learning technique, named S-Net, to correct the susceptibility artifacts the reversed-PE image pair. The proposed S-Net consists of two components: (i) a convolutional neural network to map a reversed-PE image pair to the displacement field; and (ii) a spatial transform unit to unwarp the input images and produce the corrected images. The S-Net is trained using a set of reversed-PE image pairs and an unsupervised loss function, without ground-truth data. For a new image pair of reversed-PE images, the displacement field and corrected images are obtained simultaneously by evaluating the trained S-Net directly. Evaluations on three different datasets demonstrate that S-Net can correct the susceptibility artifacts in the reversed-PE images. Compared with two state-of-the-art SAC methods (TOPUP and TISAC), the proposed S-Net runs significantly faster: 20 times faster than TISAC and 369 times faster than TOPUP, while achieving a similar correction accuracy. Consequently, S-Net accelerates the medical image processing pipelines and makes the real-time correction for MRI scanners feasible. Our proposed technique also opens up a new direction in learning-based SAC.     

Double-Color-Image Compression-Encryption Algorithm Based on Quaternion Multiple Parameter DFrAT and Feature Fusion with Preferable Restoration Quality

To achieve multiple color images encryption, a secure double-color-image encryption algorithm is designed based on the quaternion multiple parameter discrete fractional angular transform (QMPDFrAT), a nonlinear operation and a plaintext-related joint permutation-diffusion mechanism. QMPDFrAT is first defined and then applied to encrypt multiple color images. In the designed algorithm, the low-frequency and high-frequency sub-bands of the three color components of each plaintext image are obtained by two-dimensional discrete wavelet transform. Then, the high-frequency sub-bands are further made sparse and the main features of these sub-bands are extracted by a Zigzag scan. Subsequently, all the low-frequency sub-bands and high-frequency fusion images are represented as three quaternion signals, which are modulated by the proposed QMPDFrAT with three quaternion random phase masks, respectively. The spherical transform, as a nonlinear operation, is followed to nonlinearly make the three transform results interact. For better security, a joint permutation-diffusion mechanism based on plaintext-related random pixel insertion is performed on the three intermediate outputs to yield the final encryption image. Compared with many similar color image compression-encryption schemes, the proposed algorithm can encrypt double-color-image with higher quality of image reconstruction. Numerical simulation results demonstrate that the proposed double-color-image encryption algorithm is feasibility and achieves high security.     

一种基于时空变换和压缩感知的磁共振螺旋采样的图像重建算法

螺旋采样磁共振快速成像在功能性成像、并行成像和动态成像等领域发挥着越来越重要的作用.螺旋采样图像重建的传统算法是用核函数将螺旋状分布的k空间数据插值到均匀网格中,再利用傅里叶变换和最小二乘法进行重建.但是基于网格化的算法对核函数过于依赖,在网格化过程中产生难以避免的误差.该文提出了基于时空变换和压缩感知的l1范数的最优化模型和重建算法.时空变换矩阵描述了空间上的磁共振图像与采集到的时域信号间的关系,使得算法直接使用采集到的数据作为保真约束项,避免了网格化过程产生的误差.此外,基于图像处理单元的并行计算被用来提高时空变换矩阵的运算速度,使得算法具有较强的应用价值.     

A two-phase face recognition method in frequency domain

In this paper, we propose a two-phase face recognition method in frequency domain using discrete cosine transform (DCT) and discrete Fourier transform (DFT). The absolute values of DCT coefficients or DFT amplitude spectra are used to represent the face image, i.e. the transformed image. Then a two-phase face classification method is applied to the transformed images. This method is as follows: its first phase uses the Euclidean distance formula to calculate the distance between a test sample and each sample in the training sets, and then exploits the Euclidean distance of each training sample to determine K nearest neighbors for the test sample. Its second phase represents the test sample as a linear combination of the determined K nearest neighbors and uses the representation result to perform classification. In addition, we use various numbers of DCT coefficients and DFT amplitude spectra to test the effect on our algorithms. The experimental results show that our method outperforms the two-phase face recognition method based on space domain of face images.     

Position multiplexing multiple-image encryption using cascaded phase-only masks in Fresnel transform domain

A position multiplexing method based on the modified Gerchberg-Saxton algorithm (MGSA) and a cascaded phase modulation scheme in the Fresnel transform domain is proposed in the multiple-image-encryption framework. First of all, each plain image is encoded into a complex function using the MGSA. The phase components of the created complex functions are then multiplexed with different position parameters, and summed. The phase part of the summation result is recorded in the first phase-only mask (POM). The MGSA is applied on the amplitude part of the summation result to determine another phase only function which is then recorded in the second POM. The simulation results show that the crosstalk between multiplexed images is significantly reduced compared with an existing similar method [20]. Therefore, the multiplexing capacity in encrypting multiple grayscale images can be increased accordingly.     

Image encryption algorithm based on the multi-order discrete fractional Mellin transform

A multi-order discrete fractional Mellin transform (MODFrMT) is constructed and directly used to encrypt the private images. The MODFrMT is a generalization of the fractional Mellin transform (FrMT) and is derived by transforming the image with multi-order discrete fractional Fourier transform (MODFrFT) in log-polar coordinates, where the MODFrFT is generalized from the closed-form expression of the discrete fractional Fourier transform (DFrFT) and can be calculated by fast Fourier transform (FFT) to reduce the computation burden. The fractional order vectors of the MODFrMT are sensitive enough to be the keys, and consequently key space of the encryption system is enlarged. The proposed image encryption algorithm has significant ability to resist some common attacks like known-plaintext attack, chosen-plaintext attack, etc. due to the nonlinear property of the MODFrMT. Additionally, Kaplan-Yorke map is employed in coordinate transformation process of the MODFrMT to further enhance the security of the encryption system. The computer simulation results show that the proposed encryption algorithm is feasible, secure and robust to noise attack and occlusion.     

从电子显微镜的象面和衍射面强度复原相位的计算实例

高分辨率电子显微学中相位复原问题是一个重要问题。本文的计算表明,对于振幅为常数或线性函数,相位为抛物型、正弦型或指数型的波函数,可以采用Gerchberg-Saxton迭代算法从已知的象面和衍射面上的强度分布来唯一地和精确地复原真实的相位。我们编制了计算机程序,对于给定的象面波函数,采用离散的快速傅里叶算法,可以计算其衍射面的波函数。输入数值在-π,+π间的初始相位后,按照G-S迭代算法,利用本程序可以复原相位。文中详细给出了若干个计算实例。所得的相位迭代解对于1弧度的初始相位扰动是稳定的。 关键词：     

有损压缩JPEG在载频条纹图分析中的应用研究

探讨了基于JPEG的有损压缩方法在载频条纹图分析中的应用前景。简介了当今流行的JPEG有损压缩技术和傅里叶变换轮廓术。使用专业软件对傅里叶变换轮廓术中拍摄的载频条纹图进行各种压缩比的压缩,解压后再解调出相位,与未经压缩的原图解调出的相位进行比较。将其相位误差与相位移法解调出的相位误差进行了对比,指出相对于相位移法而言,傅里叶变换轮廓术具有滤波的作用,对其拍摄的载频条纹图,应用JPEG压缩算法是可能的,解调出来的相位误差更小。     

Phase correction-based singularity function analysis for partial k-space reconstruction

Partial k-space acquisition is a conventional method in magnetic resonance imaging (MRI) for reducing imaging time while maintaining image quality. In this field, image reconstruction from partial k-space is a key issue. This paper proposes an approach fundamentally different from traditional techniques for reconstructing magnetic resonance (MR) images from partial k-space. It uses a so-called singularity function analysis (SFA) model based on phase correction. With such a reconstruction approach, some nonacquired negative spatial frequencies are first recovered by means of phase correction and Hermitian symmetry property, and then the other nonacquired negative and/or positive spatial frequencies are estimated using the mathematical SFA model. The method is particularly suitable for asymmetrical partial k-space acquisition owing to its ability of overcoming reconstruction limitations due to k-space truncations. The performance of this approach is evaluated using both simulated and real MR brain images, and compared with existing techniques. The results demonstrate that the proposed SFA based on phase correction achieves higher image quality than the initial SFA or the projection-onto-convex sets (POCS) method.     

基于随机分数傅里叶变换的双图像加密算法

利用光学随机分数傅里叶变换设计了一种双图像加密算法,并给出了相应的光学实现.加密算法中,将两幅原始图像分别作为加密系统输入复函数的振幅和位相分布函数,利用随机分数傅里叶变换进行加密,所得复函数的振幅即为加密图像,而位相部分是变换的输出相位,随机位相作为加密算法的密码.在数值模拟中,二值文本图像和灰度图像分别被作为原始图像用于加密结果分析和加密安全测试,结果表明该加密算法具有很好的安全性.     

Double-image self-encoding and hiding based on phase-truncated Fourier transforms and phase retrieval

We propose a method to encrypt two covert images into an overt image based on phase-truncated Fourier transforms and phase retrieval. In this method, the two original images are self-encoded in the manner that one of the two images is directly separated into two phase masks (PMs) and used as keys for encryption, and then multiplied by a PM which is generated by using phase retrieval algorithm. At last, the whole encryption process is completed by a Fourier transform operation. In the decryption process, the image without a separation and the two PMs used as keys for encryption are all treated as encoded data. The cryptosystem is asymmetric which means the keys for encryption are different from those for decryption. Numerical simulations are presented to show the viability and good performance of the proposed method.     

Current-induced magnetic resonance phase imaging

Electric current-induced phase alternations have been imaged by fast magnetic resonance image (MRI) technology. We measured the magnetic resonance phase images induced by pulsed current stimulation from a phantom and detected its sensitivity. The pulsed current-induced phase image demonstrated the feasibility to detect phase changes of the proton magnetic resonance signal that could mimic neuronal firing. At the present experimental setting, a magnetic field strength change of 1.7 +/- 0.3 nT can be detected. We also calculated the averaged value of the magnetic flux density BT parallel to B0 produced by electric current I inside the voxel as a function of the wire position. The results of the calculation were consistent with our observation that for the same experimental setting the current-induced phase change could vary with location of the wire inside the voxel. We discuss our findings in terms of possible direct MRI detection of neuronal activity.     

A novel approach for characterizing the nonlinear phase steps of the PZT in interferometry

We propose a novel approach to estimate the phase distribution in the presence of nonlinear response of the PZT. The proposed method is an outcome of two different concepts based on the discrete chirp Fourier transform (DCFT) and the maximum-likelihood estimator for the estimation of nonlinear phase step. The robustness of the proposed method is tested for various magnitudes of nonlinearity and harmonics. Comparison of our proposed method with the bench marking algorithm by Hibino et al.'s six and nine sample algorithm in the presence of noise shows that our method is highly efficient.     

Automatic phasing of MR images. Part I: linearly varying phase

In spin-echo and well shimmed gradient-echo images, the phase of the complex image often varies linearly in both the readout and phase-encode directions. Thus, in principle, it is possible to display an image in absorption mode. However, manually determining the two first-order and one zero-order phase parameters needed to display an absorption-mode image is a formidable task. In this paper, the Bayesian calculations needed to automatically determine these parameters are presented, and the calculations are illustrated using spin-echo images.     

Enhanced Optical Image Verification Based on Joint Transform Correlator Adopting Fourier Hologram

In this paper two new architectures for optical image verification are proposed. Both architectures are based on conventional joint transform correlators (JTCs) adopting a Fourier hologram and can significantly improve the recovered image quality. First, an input phase-only function is Fourier transformed and then interferes with a reference wave that is diffracted from a plane wave incident on another random phase mask. Second, two phase-only functions are placed at the two input sides of a beamsplitter such that the interference pattern of their Fourier transforms can be detected. To obtain a predefined target image in the output plane, one of the input phase functions is iteratively retrieved by the use of the projection onto constraint sets algorithm. Simulation results show that the less mean squared error and better image quality are obtained for both the binary and grayscale images.     

Optical image encryption using fractional Fourier transform and chaos

We propose a new method for image encryption using fractional Fourier transform and chaos theory. Random phase masks are generated using iterative chaos functions. The input image is combined with the first random phase mask at the object plane and is then transformed using the fractional Fourier transform. After the first fractional Fourier transform, the second random phase mask, again generated by using the chaos functions, is used at the fractional plane. The second fractional Fourier transform operation is then carried out to obtain the encrypted image. Three types of chaos functions have been used: the logistic map, the tent map and the Kaplan–Yorke map. The mean square error and the signal-to-noise ratio between the decrypted image and the input image for the correct order and the incorrect order of the fractional Fourier transform have been calculated. The computer simulations are presented to verify the validity of the proposed technique.     

基于相位相关性的傅里叶变换光谱数据的相位误差修正方法

 相位误差的校正是傅里叶变换成像光谱仪数据处理的重要环节之一。针对干涉曲线的对称性特征,利用相位相关性计算方法,提出一种新的傅里叶变换光谱数据的相位校正的方法。将相位相关性拟合为Sinc函数,计算亚像素的偏移量,采用离散余弦变换转换到光谱域。使用标准光谱库中的源光谱数据作为原始数据,将通过离散余弦变换仿真的干涉数据与该方法得到的结果进行比较和验证,并与Mertz方法进行了对比。结果表明：该方法精度优于Mertz方法,并且计算简单。     

基于相位相关的匀速直线运动模糊图像位移参数估计

为估算匀速直线运动模糊图像的运动参数,提出了一种基于相位相关分析的图像配准方法。该方法利用傅里叶变换的平移特性,对产生平移的目标图像进行傅里叶变换并计算归一化互功率谱,其傅里叶逆变换对应二维脉冲函数,通过计算脉冲函数峰值坐标获取位移图像之间的亚像元级位移量。结合相位相关配准原理和线性空间不变退化模型,给出了匀速直线运动点扩散函数及其光学传递函数的数学描述;讨论了匀速直线运动模糊对相位相关配准结果的影响,证明了图像经过匀速直线运动退化后,位移图像之间归一化互功率谱具有不变性。实验结果表明：动态运动模糊图像最大检测误差为0.489 pixel,标准差为0.16 pixel。