Joint Estimation and Correction of Geometric Distortions for EPI Functional MRI Using Harmonic Retrieval

Magnetic resonance imaging (MRI) uses applied spatial variations in the magnetic field to encode spatial position. Therefore, nonuniformities in the main magnetic field can cause image distortions. In order to correct the image distortions, it is desirable to simultaneously acquire data with a field map in registration. We propose a joint estimation (JE) framework with a fast, noniterative approach using harmonic retrieval (HR) methods, combined with a multi-echo echo-planar imaging (EPI) acquisition. The connection with HR establishes an elegant framework to solve the JE problem through a sequence of 1-D HR problems in which efficient solutions are available. We also derive the condition on the smoothness of the field map in order for HR techniques to recover the image with high signal-to-noise ratio. Compared to other dynamic field mapping methods, this method is not constrained by the absolute level of the field inhomogeneity over the slice, but relies on a generous pixel-to-pixel smoothness. Moreover, this method can recover image, field map, and T2* map simultaneously.      

Special Phenomena of the Shadow Region in the High Resolution Synthetic Aperture Radar Image due to Synthetic Aperture

With the development of several High Resolution (HR) Synthetic Aperture Radar (SAR) systems, many special phenomena appear in the SAR image, especially for the SAR image with millimeter wave. We firmly believed that every detail in the SAR image should have its own special mechanisms and these details may provide some key clues for us to build up the frame work on understanding the SAR image. The synthetic aperture is one of the important particularities about SAR, and the radar is moving during the data is collected, which leads many special phenomena in the SAR image; one of these is the shadow with blurred boundary. In this work, the effect on the shadow region in the SAR image by synthetic aperture is expanded on. The blurred boundary of the shadow is analyzed using imaging formation theory, and the Quadratic Phase Errors (QPE) brought by the synthetic aperture progress is deduced for the first time, which builds up the relationship between the parameters of the shadow caster and the behavior of the shadow in the SAR image. It is found that the QPE is approximately a linear function of the height of the shadow caster. Furthermore, an approach for shadow enhancement based on height variant phase compensation is proposed and it could provide a better effect on shadow enhancement than the traditional technique called Fixed Focus Shadow Enhancement (FFSE), which is proved by theoretical analysis and experiments. Based on the analysis, some typical application of the shadow in SAR image is designed and some mini-SAR image with Ku-band is analyzed about the shadow region. It is expected that the work in this paper could be some helpful for the SAR image understanding and the microwave imaging with high resolution.     

Design and fabrication of sub-μs silicon-on-insulator thermo-optic 4×4 switch matrix

A rearrangeable nonblocking silicon-on-insulator-based thermo-optic 4x4 switch matrix with spot size converters （SSCs） and a new driving circuit are designed and fabricated. The introduction of a spot size converter （SSC） has decreased the insertion loss to less than 10dB and the new driving circuit has improved the response speed to less than l~s.     

Dynamic programming implementation on array processor architectures

Dynamic Programming (DP) applies to many signal and image processing applications including boundary following, the Viterbi algorithm, dynamic time warping, etc. This paper presents an array processor implementation of generic dynamic programming. Our architecture is a SIMD array attached to a host computer. The processing element of the architecture is based on an ASIC design opting for maximum speed-up. By adopting a torus interconnection network, a dual buffer structure, and a multilevel pipeline, the performance of the DP chip is expected to reach the order of several GOPS. The paper discusses both the dedicated hardware design and the data flow control of the DP chip and the total array.This work was supported in part by the NATO, Scientific and Environmental Affairs Division, Collaborative Research Grant SA.5-2-05(CRG.960201)424/96/JARC-501.     

Recursive high-resolution reconstruction of blurred multiframeimages

An approach to obtaining high-resolution image reconstruction from low-resolution, blurred, and noisy multiple-input frames is presented. A recursive-least-squares approach with iterative regularization is developed in the discrete Fourier transform (DFT) domain. When the input frames are processed recursively, the reconstruction does not converge in general due to the measurement noise and ill-conditioned nature of the deblurring. Through the iterative update of the regularization function and the proper choice of the regularization parameter, good high-resolution reconstructions of low-resolution, blurred, and noisy input frames are obtained. The proposed algorithm minimizes the computational requirements and provides a parallel computation structure since the reconstruction is done independently for each DFT element. Computer simulations demonstrate the performance of the algorithm.     

High resolution image formation from low resolution frames using Delaunay triangulation

An algorithm based on spatial tessellation and approximation of each triangle patch in the Delaunay (1934) triangulation (with smoothness constraints) by a bivariate polynomial is advanced to construct a high resolution (HR) high quality image from a set of low resolution (LR) frames. The high resolution algorithm is accompanied by a site-insertion algorithm for update of the initial HR image with the availability of more LR frames till the desired image quality is attained. This algorithm, followed by post filtering, is suitable for real-time image sequence processing because of the fast expected (average) time construction of Delaunay triangulation and the local update feature.     

A lattice realization for 2-D separable-denominator digital filters

New properties useful in connection with 1-D and 2-D lattice realizations are developed. These properties enable one to represent given, complicated 2-D separable-denominator digital filters in terms of simpler, more elemental building blocks which consist of two 1-D lattice realizations having dynamics in different directions and connected in a cascade form. The matrix-relationship between a 2-D discrete Schwarz form and a controller-observer canonical form is also derived. A notable property of the proposed 2-D lattice realization is that the impulse response energy of a 2-D separable-denominator digital filter can be readily obtained from the reflection coefficients and input/output tapped coefficients of the realization.This work was supported by the National Science Council of the Republic of China under Grant NSC79-0402-E0006-02, the US Army Research Office under Grant DAAL-03-91-G0106, and the NASA-Johnson Space Center under Grant NAG-9-380.     

Nonparametric spectral analysis of gapped data via an adaptive filtering approach

We present an algorithm for nonparametric complex spectral analysis of gapped data via an adaptive finite impulse response (FIR) filtering approach, referred to as the gapped-data amplitude and phase estimation (GAPES) algorithm. The incomplete data sequence may contain gaps of various sizes. The GAPES algorithm iterates the following two steps: (1) estimating the adaptive FIR filter and the corresponding complex spectrum via amplitude and phase estimation (APES), a nonparametric adaptive FIR filtering approach, and (2) filling in the gaps via a least-squares APES fitting criterion. The initial condition for the iteration is obtained from the available data segments via APES. Numerical results are presented to demonstrate the effectiveness of the proposed GAPES algorithm.This work was supported in part by the Senior Individual Grant Program of the Swedish Foundation for Strategic Research, AFRL/SNAT, Air Force Research Laboratory, Air Force Material Command, USAF, under grant number F33615-99-1-1507, and the National Science Foundation Grant MIP-9457388. The US Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notice thereon.     

基于边界像素的模糊模型复原研究

针对水平方向匀速直线运动模糊一般模型进行复原时存在明显周期干扰的问题,从分析边缘像素的角度出发,提出了基于零边界像素的复原模型和基于Neumann边界像素的复原模型,有效的减轻了周期干扰.通过广义逆矩阵进行运动模糊图像的复原,从实验结果来看,本文的复原方法简单可行,并具有较好的复原效果.     

一种高精度的压缩域视频目标分割算法

该文提出了一种工作于MPEG压缩域的快速视频目标分割算法。该算法以从MPEG1/2码流中部分解码提取的特征为输入,提取P帧中的运动目标。针对一般的压缩域算法目标边界精度不高的特点,算法采用I帧和P帧中每个块的直流DCT系数和3个交流DCT系数,以及运动补偿信息,重建出P帧的原图像1/16大小的子图像,采用快速平均移聚类得到具有较高边界精度的亮度一致的区域;针对运动向量的噪声容易造成错误检测的缺点,算法结合聚类分析结果和运动块的分布,采用基于马尔可夫随机场的统计标号方法对目标和背景区域进行分类,得到每个P帧的目标掩模。该算法可以得到44子块的边界精度,对于CIF格式的码流,在Pentium IV 2GHz平台上可以达到每秒40帧的处理速度。     

Polynomial ambiguity resistant precoders: Theory and applications in ISI/multipath cancellation

In this paper, precoding techniques are studied for combating the intersymbol interference (ISI)/multipath effects in communication systems. We introduce a new type-precoder which we term thepolynomial ambiguity resistant (PAR) precoder for its ability to resist signal distortion induced by finite impulse response (FIR) channels. In particular, the precoder allows a receiver to identify an input signal without knowing the channel characteristics at the expense of a minimum amount of bandwidth increase. A family of such precoders, which is linear (no modulo operations), channel independent, and modulation pattern preserving (except for some occasional 0 symbols), is presented. Also presented is a closed-form algorithm that can simultaneously identify the input signals and zero-forcing equalizers.Work supported in part by the Air Force Office of Scientific Research (AFOSR) under Grant No. F49620-97-1-0253 and F49620-98-1-0352, the National Science Foundation CAREER Program under Grant MIP-9703377, and the University of Delaware Research Foundation.Work supported in part by the Air Force Office of Scientific Research (AFOSR) under Grant No. F49620-97-1-0318, the Office of Naval Research (ONR) under Grant No. N00014-97-1-0475, and the National Science Foundation CAREER Program under Grant MIP-9703074.     

Depth-first coding for multivalued pictures using bit-planedecomposition

A data compression technique using a bit-plane decomposition strategy of multivalued images is described. Although the bit-plane decomposition is mainly used for image transmission, our method takes the image expression for image database into consideration. It has two merits which are a hierarchical representation using depth-first (DF) expression and a simple noise reduction algorithm for the DF expression that is similar to human perception. The DF expression is useful for image expansion, rotation, etc. We study the information in an image that should be eliminated by noise reduction. Noise-like patterns in an image are uniformalized and the edge and smooth surfaces remain nearly unchanged. They are not blurred, but instead are a little enhanced. We also study the properties of the black-and-white (B/W) boundary points on bit-planes. The algorithm of the uniformalization process with a DF-expression of an image is described. An experiment for real image data is carried out by a comparison to other methods, and the results are discussed     

Blind identification of multichannel FIR blurs and perfect imagerestoration

Despite its practical importance in image processing and computer vision, blind blur identification and blind image restoration have so far been addressed under restrictive assumptions such as all-pole stationary image models blurred by zero or minimum-phase point-spread functions. Relying upon diversity (availability of a sufficient number of multiple blurred images), we develop blind FIR blur identification and order determination schemes. Apart from a minimal persistence of the excitation condition (also present with nonblind setups), the inaccessible input image is allowed to be deterministic or random and of unknown color of distribution. With the blurs satisfying a certain co-primeness condition in addition, we establish existence and uniqueness results which guarantee that single input/multiple-output FIR blurred images can be restored blindly, though perfectly in the absence of noise, using linear FIR filters. Results of simulations employing the blind order determination, blind blur identification, and blind image restoration algorithms are presented. When the SNR is high, direct image restoration is found to yield better results than indirect image restoration which employs the estimated blurs. In low SNR, indirect image restoration performs well while the direct restoration results vary with the delay but improve with larger equalizer orders.     

On the concentrated stochastic likelihood function in array signal processing

The stochastic likelihood function [(STO)LF] associated with the narrowband signal processing problem can be concentrated with respect to the signal covariance matrix elements and the noise power. Although this is a known fact, no clear-cut derivation of the concentrated (STO)LF appears to be available in the literature. In this short paper we provide a simple, complete proof of the concentrated (STO)LF formula.The work of A. Nehorai was supported by the Air Force Office of Scientific Research under Grant no. F49620-93-1-0096, the Office of Naval Research under Grant no. N00014-91-J-1298, and the National Science Foundation under grant no. MIP-9122753. The work of P. Stoica was supported by the Swedish Research Council for Engineering Sciences under contract no. 93-669.     

Video super-resolution reconstruction based on deep convolutional neural network and spatio-temporal similarity

Existing learning-based super-resolution (SR) reconstruction algorithms are mainly designed for single image, which ignore the spatio-temporal relationship between video frames. Aiming at applying the advantages of learning-based algorithms to video SR field, a novel video SR reconstruction algorithm based on deep convolutional neural network (CNN) and spatio-temporal similarity (STCNN-SR) was proposed in this paper. It is a deep learning method for video SR reconstruction, which considers not only the mapping relationship among associated low-resolution (LR) and high-resolution (HR) image blocks, but also the spatio-temporal non-local complementary and redundant information between adjacent low-resolution video frames. The reconstruction speed can be improved obviously with the pre-trained end-to-end reconstructed coefficients. Moreover, the performance of video SR will be further improved by the optimization process with spatio-temporal similarity. Experimental results demonstrated that the proposed algorithm achieves a competitive SR quality on both subjective and objective evaluations, when compared to other state-of-the-art algorithms.     

基于序列间先验约束和多视角信息融合的肝脏CT图像分割

医学电子计算机断层扫描(CT)序列图像中肝脏的准确分割是实现计算机辅助肝手术的重要前提,然而图像中存在的组织病变、边界模糊或缺失、不同组织间的粘连给肝脏分割带来极大挑战。针对这些问题,该文提出一种基于图像序列间先验约束的半自动分割方法,并进一步采取了多视角信息融合的方式实现肝脏的准确分割。该方法的优势在于无需大量数据的收集和复杂的先验训练。在Sliver07公开数据集合的验证结果显示,和领域内主要方法相比,该方法具有较高的分割准确度,特别是当肝脏区域存在病灶、边界模糊或缺失的情况下具有明显提升。     

A MAP approach for joint motion estimation, segmentation, and super resolution.

Super resolution image reconstruction allows the recovery of a high-resolution (HR) image from several low-resolution images that are noisy, blurred, and down sampled. In this paper, we present a joint formulation for a complex super-resolution problem in which the scenes contain multiple independently moving objects. This formulation is built upon the maximum a posteriori (MAP) framework, which judiciously combines motion estimation, segmentation, and super resolution together. A cyclic coordinate descent optimization procedure is used to solve the MAP formulation, in which the motion fields, segmentation fields, and HR images are found in an alternate manner given the two others, respectively. Specifically, the gradient-based methods are employed to solve the HR image and motion fields, and an iterated conditional mode optimization method to obtain the segmentation fields. The proposed algorithm has been tested using a synthetic image sequence, the "Mobile and Calendar" sequence, and the original "Motorcycle and Car" sequence. The experiment results and error analyses verify the efficacy of this algorithm.     

基于Neumann边界条件的图像局部复原

图像复原是图像处理中的一个重要课题。人们通常将其当作全局问题来处理,这可能会导致非常庞大而不可行的l2问题。为了克服这个困难,本文提出一种新的局部图像复原算法;将大的降晰图像分成若干子图像块,分别对各块进行复原。该算法用经典的Tikhonov正则化方法求解病态反问题。为了抑制分块导致的边界噪声,算法引入Neumann边界条件和块部分重叠的思想。实验结果表明,该算法有效地降低了图像处理的复杂度,而且与全局算法相比,两者复原图像的质量很接近。     

高速运动目标的运动模糊图像复原研究

对单一图像进行运动模糊复原,存在模糊点扩散函数（PSF）难以估计以及图像反卷积的病态性问题。利用多个PSF具有联合可逆性的特点,针对运动目标观测,提出采用参数相同的多个成像设备共同对同一视场进行拍摄,来获取背景相同、曝光时间不同、目标模糊程度不同的观测图像;然后利用同一设备获取的序列图像进行目标的模糊PSF估计;并根据目标背景的运动模糊叠加特征,分别从观测图像中提取出完整的模糊目标图像;最后,对这些具有不同PSF的同一目标图像进行空间域迭代复原算式的联立求解。实验表明:该方法设计的目标获取装置对硬件条件要求较低,获取的图像更便于采用多点扩散函数联合进行图像复原,复原效果良好。     

On the application of a modified self-organizing neural network to estimate stereo disparity.

We propose a modified self-organizing neural network to estimate the disparity map from a stereo pair of images. Novelty consists of the network architecture and of dispensing with the standard assumption of epipolar geometry. Quite distinct from the existing algorithms which, typically, involve area- and/or feature-matching, the network is first initialized to the right image, and then deformed until it is transformed into the left image, or vice versa, this deformation itself being the measure of disparity. Illustrative examples include two classes of stereo pairs: synthetic and natural (including random-dot stereograms and wire frames) and distorted. The latter has one of the following special characteristics: one image is blurred, one image is of a different size, there are salient features like discontinuous depth values at boundaries and surface wrinkles, and there exist occluded and half-occluded regions. While these examples serve, in general, to demonstrate that the technique performs better than many existing algorithms, the above-mentioned stereo pairs (in particular, the last two) bring out some of its limitations, thereby serving as possible motivation for further work.