Estimation of dense image flow fields in fluids

The estimation of flow fields from time sequences of satellite imagery has a number of important applications. For visualization of cloud or sea ice movements in sequences of crude temporal sampling, a satisfactory nonblurred temporal interpolation can be performed only when the flow field or an estimate thereof is known. Estimated flow fields in weather satellite imagery might also be used on an operational basis as inputs to short-term weather prediction. The authors describe a method for the estimation of dense flow fields. Local measurements of motion are obtained by analysis of the local energy distribution, which is sampled by using a set of three-dimensional (3D) spatio-temporal filters. The estimated local energy distribution also allows the authors to compute a confidence measure of the estimated local normal flow. The algorithm, furthermore, utilizes Markovian random fields in order to integrate the local estimates of normal flows into a dense flow field by using measures of spatial smoothness. To obtain smoothness, the authors will constrain first-order derivatives of the flow field. The performance of the algorithm is illustrated by the estimation of the flow fields corresponding to a sequence of Meteosat thermal images. The estimated flow fields are used in a temporal interpolation scheme     

Super-resolution in PET imaging

This paper demonstrates a super-resolution method for improving the resolution in clinical positron emission tomography (PET) scanners. Super-resolution images were obtained by combining four data sets with spatial shifts between consecutive acquisitions and applying an iterative algorithm. Super-resolution attenuation corrected PET scans of a phantom were obtained using the two-dimensional and three-dimensional (3-D) acquisition modes of a clinical PET/computed tomography (CT) scanner (Discovery LS, GEMS). In a patient study, following a standard 18F-FDG PET/CT scan, a super-resolution scan around one small lesion was performed using axial shifts without increasing the patient radiation exposure. In the phantom study, smaller features (3 mm) could be resolved axially with the super-resolution method than without (6 mm). The super-resolution images had better resolution than the original images and provided higher contrast ratios in coronal images and in 3-D acquisition transaxial images. The coronal super-resolution images had superior resolution and contrast ratios compared to images reconstructed by merely interleaving the data to the proper axial location. In the patient study, super-resolution reconstructions displayed a more localized 18F-FDG uptake. A new approach for improving the resolution of PET images using a super-resolution method has been developed and experimentally confirmed, employing a clinical scanner. The improvement in axial resolution requires no changes in hardware.     

基于Lorentzian范数的图像超分辨率重建

本文在MAP随机正则化技术估计框架下,提出了一种基于Lorentzian范数估计和自适应核回归正则项的最小化代价函数。此算法对不同假设类型的噪声模型不敏感,鲁棒性较好。实验结果证明了本文方法不仅能有效提高图像清晰度,且与其它方法相比,去噪能力更强,边缘保持较好。     

Effect of settlement on dense slurry flow in a horizontal channel

A shear viscosity model for the underfill flow is proposed based on slug flow, which is appropriate in the case of neutrally buoyant particles. However, the filling particles used in practice are often heavier than the liquid carriers. The effect of non-neutrally buoyant particles is investigated in this work. The flow of dense slurry in which the filling particles are heavier than the liquid carrier is analyzed by considering the particle-particle and particle-wall interactions, which are derived from fluid film lubrication theory. The effect of settlement causes the flow behavior to depart from that of slug flow. Nevertheless, steady flow is still found possible, and, for a few representative packing patterns considered, somewhat modified flow patterns exist.     

一种改进的超分辨率算法

利用多帧低分辨率图像重建一幅高分辨率图像成为迫切需要解决的难题,传统基于插值的超分辨率算法的发展受到了限制。本文基于重建方法,根据低分辨率图像帧间运动参数,提出了合理的权重分配算法。实验结果表明,图像超分辨率重建取得了良好效果。     

超分辨测高的试验研究

多径信号的存在,使得米波雷达在低仰角的测高成为难题。随着空间谱估计技术的发展,人们尝试采用阵列超分辨方法实现米波雷达的仰角维方向估计。简要介绍了常规测高法的局限性和角度超分辨实现测高的基本原理,以及在米波雷达中开展的测高试验情况,给出了若干淡水反射面条件下的外场试验数据。对多批目标的试验统计结果表明:在快拍数只有一个、单个阵元平均信噪比达到8dB以上时,采用空间平滑+最大似然超分辨处理法即可有效分离相干信号源、减小米波雷达在低仰角的测高误差。     

Super-resolution reconstruction of hyperspectral images.

Hyperspectral images are used for aerial and space imagery applications, including target detection, tracking, agricultural, and natural resource exploration. Unfortunately, atmospheric scattering, secondary illumination, changing viewing angles, and sensor noise degrade the quality of these images. Improving their resolution has a high payoff, but applying super-resolution techniques separately to every spectral band is problematic for two main reasons. First, the number of spectral bands can be in the hundreds, which increases the computational load excessively. Second, considering the bands separately does not make use of the information that is present across them. Furthermore, separate band super-resolution does not make use of the inherent low dimensionality of the spectral data, which can effectively be used to improve the robustness against noise. In this paper, we introduce a novel super-resolution method for hyperspectral images. An integral part of our work is to model the hyperspectral image acquisition process. We propose a model that enables us to represent the hyperspectral observations from different wavelengths as weighted linear combinations of a small number of basis image planes. Then, a method for applying super resolution to hyperspectral images using this model is presented. The method fuses information from multiple observations and spectral bands to improve spatial resolution and reconstruct the spectrum of the observed scene as a combination of a small number of spectral basis functions.     

航空图像超分辨率重构技术

为了过滤掉航空图像中的模糊因素,获取高质量的航空图像,提出基于先验信息的航空图像超分辨率重构方法,采用基于互信息的航空序列图像配准方法完成航空图像的配准,通过最大信息熵复原方法对配准后的图像序列进行去模糊处理,获取航空图像序列。利用小波变换方法使得图像序列内存在的冗余信息以及互补信息融合至一帧图像中,通过O-MOMS插值算法对融合后的单帧航空图像进行插值重构,获取高分辨率的航空图像。实验结果说明,所提方法重构出的航空图像更为清晰,具有较低的信噪比和较高的重构效率。     

Super-resolution registration using tissue-classified distance fields

We present a method for registering the position and orientation of bones across multiple computed-tomography (CT) volumes of the same subject. The method is subvoxel accurate, can operate on multiple bones within a set of volumes, and registers bones that have features commensurate in size to the voxel dimension. First, a geometric object model is extracted from a reference volume image. We use then unsupervised tissue classification to generate from each volume to be registered a super-resolution distance field--a scalar field that specifies, at each point, the signed distance from the point to a material boundary. The distance fields and the geometric bone model are finally used to register an object through the sequence of CT images. In the case of multiobject structures, we infer a motion-directed hierarchy from the distance-field information that allows us to register objects that are not within each other's capture region. We describe a validation framework and evaluate the new technique in contrast with grey-value registration. Results on human wrist data show average accuracy improvements of 74% over grey-value registration. The method is of interest to any intrasubject, same-modality registration applications where subvoxel accuracy is desired.     

图像的超分辨率处理方法研究现状

超分辨率图像处理技术是利用多帧关于同一场景的有相互位移的低分辨率降质图像来重建高分辨率高质量图像的技术.介绍了超分辨率图像处理技术的概念和起源;综述了超分辨率图像恢复研究现状.重点对单帧和多帧超分辨率图像处理的主要方法进行了评述,并总结对比了频域和空域方法的优缺点.最后对超分辨率图像处理技术的技术难点和前沿问题研究前景进行介绍和展望.     

高速超分辨率图像处理系统

为了对遥感图像进行实时脱机的超分辨率增强处理,设计了一种基于现场可编程逻辑门阵列(FPGA)和数字信号处理器(DSP)的超分辨率图像处理系统,系统在视频预处理部分利用FPGA来实现对视频的降采样处理,在超分辨率处理部分分别用FPGA和DSP来完成对视频源的两种经典超分辨率算法的硬件实现.达到了对视频图像进行高速实时超分辨率处理的目的.     

一种用于多径环境的超分辨率TOA定位算法

分析了基于来波到达时间(TOA)的定位技术中存在的问题,把时域超分辨率最小范数(Min-Norm)谱估计算法引入到频域TOA估计领域,提出了互相关Min-Norm超分辨率TOA算法,利用互相关技术理论上可消除非相关噪声对算法的影响.仿真结果表明,该算法具有超分辨率特性及强抗噪性,可在小带宽、强噪声背景下获得稳定、准确的时延估计结果,适于在多径效应严重的环境中应用.     

Super-resolution mosaicing from MPEG compressed video

In this paper we address the problem of mosaic construction from MPEG 1/2 compressed video for the purpose of video browsing. State-of-the-art mosaicing methods work on raw video, but most video content is available in compressed form such as MPEG 1/2. Applying these methods to compressed video requires full decoding which is very costly. The resulting mosaic is in general too large to display on the screen and is thus inappropriate for the purpose of video browsing. Therefore, we directly extract very low-resolution frames from MPEG 1/2 compressed video for the mosaic construction and then apply a super-resolution (SR) method based on iterative backprojections in order to increase the mosaic resolution and its visual quality. Global motion to be used in the SR method for aligning and warping the frames is estimated from motion information contained in the compressed stream. We also use the estimated global motion in the blur estimation and in the choice of the degradation model used for the restoration in the SR algorithm. The method for the SR mosaic construction from MPEG 1/2 compressed video that we present in this paper is less costly than mosaic construction from full decoded video. Furthermore, the resulting mosaic size is more appropriate for the purpose of video browsing.     

视频监控图像的超分辨率复原研究

超分辨率复原技术是一种可用于提高图像细节辨识能力的有效方法。其在视频监控领域可望得到广泛应用。超分辨率图像处理技术通过融合多帧相似的低分辨率图像达到提高图像细节的目的。从而降低对监控视频采集硬件与后端辅助处理系统的要求,提高对特定目标的辨析能力。本文重点介绍了在视频监控领域较为实用的凸集投影算法、最大后验概率估计算法、基于对象的超分辨率复原方法、基于示例学习与多类预测器的超分辨率复原方法。对以上超分辨率复原方法实现流程的优缺点与其在视频图像监控领域的应用方法进行了相应分析。分析了超分辨率视频监控图像复原常用的基于块匹配与光流的对象运动估计方法。对超分辨率复原重建图像质量的评估标准也进行了相应讨论。     

Accurate dense optical flow estimation using adaptive structure tensors and a parametric model

An accurate optical flow estimation algorithm is proposed in this paper. By combining the three-dimensional (3D) structure tensor with a parametric flow model, the optical flow estimation problem is converted to a generalized eigenvalue problem. The optical flow can be accurately estimated from the generalized eigenvectors. The confidence measure derived from the generalized eigenvalues is used to adaptively adjust the coherent motion region to further improve the accuracy. Experiments using both synthetic sequences with ground truth and real sequences illustrate our method. Comparisons with classical and recently published methods are also given to demonstrate the accuracy of our algorithm.     

基于MAP及边缘保持的超分辨率图像复原

MAP方法是解决超分辨率图像复原问题中的一种常用算法,但通常的MAP超分辨率复原方法对于图像的边缘部分没有进行特殊处理,导致最终恢复出来的高分辨率图像的边缘过于平滑.提出了一种局部边缘自适应的先验概率算子,并将其应用于MAP超分辨率图像复原中.与传统方法相比,它具有更好的图像边缘保持能力,因此获得了更佳的视觉效果.     

基于一阶范数的视频超分辨率重建

讨论了视频成像的基本模型,并在此基础上提出了一种基于一阶范数的视频图像重建算法,该方法同时对高分辨率图像和运动矢量进行迭代估计,并采用一阶范数和Robers算子对于当前普遍的采用二阶范数项作为视频数据逼近项和归整项的方式进行了改进。实验结果表明,该算法在原图像受到椒盐噪声影响的情况下,重建效果要优于二阶方法,并且该方法在重建图象的边缘保持上也有相对比较好的效果。     

多帧图像超分辨复原算法中帧的选取

研究了多帧图像超分辨复原算法中参考帧和参与复原图像帧数据集的选取问题.提出了两条参考帧选取的准则,设计了一种分步的图像配准和超分辨复原的方法.首先计算初始图像序列的运动向量参数,根据准则选取了参考帧和参与复原图像帧数据集,进而生成了新的有利于图像超分辨复原的优化的图像序列,再通过亚像素图像配准,计算得到小范围的相对精确的运动估计参数,最后用到图像超分辨复原算法中.仿真实验结果证明,本文提出的多帧图像超分辨复原算法中帧的选取方案是合理的,超分辨复原的图像质量在主观评价和客观指标上都获得了优于经典的Farsiu算法的效果.     

水下视频图像的超分辨率重建与增强

针对水下视频图像对比度低、图像模糊和噪声突出的特点,提出一种新的基于凸集投影(POCS)的超分辨率图像重建与增强算法。在POCS迭代约束的过程中,采用小波域非线性函数抑制噪声并突出细节,然后用能量非递减性约束集进行修正。实验表明,该方法具有较好的超分辨率重建与增强效果。