检索结果-内蒙古大学图书馆

2nd International Congress on image and Signal Processing

作者： Yang, Ronggen Ren, Mingwu Huaiyin Inst Technol Dept Comp Engn Huaian Peoples R China Nanjing Univ Sci & Technol Sch Comp Sci Nanjing Peoples R China

ISBN: (纸本)9781424441303

It is now well understood that it is possible to reconstruct sparse signals exactly from what appear to be highly incomplete sets of linear measurements. The form is solution to the optimization problem min parallel to s parallel to(0), subject to As = x. while this is an NP hard problem, i.e., a non convex problem, therefore researchers try to solve it by constrained l(1)-norm minimization and get near-optimal solution. In this paper, we study a novel method, called smoothed l(0) -norm, for sparse signal recovery. Unlike previous methods, our algorithm tries to directly minimize the l(0) -norm. It is experimented on synthetic and real image data and shows that the proposed algorithm outperforms the interior-point LP solvers, while providing the same even better accuracy.

关键词： compressed sensing sparse decomposition image reconstruction sparse approximation Basis pursuit

来源：评论

学校读者我要写书评

暂无评论

Accelerating Parallel Magnetic Resonance image reconstruction on Graphics Processing Units Using CUDA 2

Accelerating Parallel Magnetic Resonance Image Reconstructio...

引用

2nd IEEE International conference on Information and Computer Technologies (ICICT)

作者： Inam, Omair Qureshi, Mahmood Akram, Hamza Omer, Hammad Laraib, Zoia COMSATS Univ Islamabad Dept Elect & Comp Engn Islamabad Pakistan

ISBN: (纸本)9781728133232

Magnetic Resonance Imaging (MRI) is a non-invasive and powerful technique for clinical diagnosis and treatment monitoring. However, long data acquisition time in conventional MRI may cause patient discomfort and compliance. Recently, parallel magnetic resonance imaging (pMRI) techniques have been developed to speed-up the MR data acquisition time by collecting a reduced data set (k-space) using multi-channel receiver coils. However, with an increasing number of receiver coils, the handling and processing of a massive MR data limits the performance of pMRI techniques in terms of reconstruction time. Therefore, in real-time clinical settings, high speed systems have become imperative to meet the large data processing requirements of pMRI technique i.e. Generalized Auto-calibrating Partially Parallel Acquisition (GRAPPA). Graphics processing units (GPUs) have recently emerged as a viable solution to adhere the rising demands of fast data processing in pMRI. This work presents the GPU accelerated GRAPPA reconstruction method using optimized CUDA kernels to obtain high-speed reconstructions, where multiple threads simultaneously communicate and cooperate to exploit the fine grained parallelism of GRAPPA reconstruction process. For a fair comparison, the performance of the proposed GPU based GRAPPA reconstruction is evaluated against CPU based GRAPPA. Several experiments against various GRAPPA configuration settings are performed using 8-channel in-vivo 1.5T human head datasets. Experimental results show that the proposed method speeds up the GRAPPA reconstruction time up to 15x without compromising the image quality.

关键词： parallel image processing graphics processing unit(GPU) medical image processing high performance parallel computing

来源：评论

学校读者我要写书评

暂无评论

Deconvolution in line scanners using a-priori information

Deconvolution in line scanners using a-priori information

引用

2nd conference on image reconstruction from incomplete data

作者： Wirnitzer, B Spraggon-Hernandez, T Univ Appl Sci Mannheim D-68163 Mannheim Germany

ISBN: (纸本)0819445592

In a digital camera the MTF of the optical system must comprise a low-pass filter in order to avoid aliasing. The MTF of incoherent imaging usually and in principle is far from an ideal low-pass. Theoretically a digital ARMA-Filter can be used to compensate for this drawback. In praxis such deconvolution filters suffer from instability because of time-variant noise and space-variance of the MTF. In addition in a line scanner the MTF in scan direction slightly differs in each scanned image. Therefore inverse filtering will not operate satisfactory in an unknown environment. A new concept is presented which solves both problems using a-priori information about an object, e.g. that parts of it are known to be binary. This information is enough to achieve a stable space and time-variant ARMA-deconvolution filter. Best results are achieved using non linear filtering and pattern feedback. The new method was used to improve the bit-error-rate (BER) of a high-density matrix-code scanner by more than one order of magnitude. An audio scanner will be demonstrated, which reads 12 seconds of music in CD-quality from an audio coded image of 18mmx55mm size.

关键词： image deconvolution decision feedback non-linear filter two dimensional adaptive filter

来源：评论

学校读者我要写书评

暂无评论

Generalized support constraint for three-dimensional reconstruction from incomplete Fourier spectra

引用

JOURNAL OF ELECTRONIC IMAGING 1997年第4期6卷 426-438页

作者： Payot, E Preteux, FJ Trousset, Y Guillemaud, R CEA LETI DSYS F-38054 Grenoble 9 France Inst Natl Telecommun F-91011 Evry France G E Med Syst F-78533 Buc France

Many imaging systems involve a loss of information that requires the incorporation of prior knowledge in the restoration/reconstruction process. We focus on the typical case of 30 reconstruction from an incomplete set of projections. An approach based an constrained optimization is introduced This approach provides a powerful mathematical framework for selecting a specific solution from the set of feasible solutions;this is done by minimizing some criteria depending on prior densitometric information that can be interpreted through a generalized support constraint. We propose a global optimization scheme using a deterministic relaxation algorithm based on Bregman's algorithm associated with half-quadratic minimization techniques. When used for 30 vascular reconstruction from 2D digital subtracted angiography (DSA) data, such an approach enables the reconstruction of a well-contrasted 30 vascular network in comparison with results obtained using standard algorithms. (C) 1997 SPIE and IS&T.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Experiments of super-resolution utilizing sub-pixel shifted overlapping images

Experiments of super-resolution utilizing sub-pixel shifted ...

引用

26th Asian conference on Remote Sensing, ACRS 2005 and 2nd Asian Space conference, ASC

作者： Shimoda, Haruhisa Fukue, Kiyonari Tokai University Research and Information Center 2-28-4 Tomigaya Tokyo 151-0063 Japan

ISBN: (纸本)9781604237511

Experiments for superresolution image reconstruction from subpixel shifted overlapping images has been performed for computer simulated image data in order to evaluate the primitive superresolution image reconstruction methods. The methods based on simultaneous equation showed comparatively small rms error according to the numerical solution. However, a high-resolution image was not obtained at ill-conditioned. The method based on local iteration showed good performance from view point of rms error and robustness.

关键词： Iterative methods

来源：评论

学校读者我要写书评

暂无评论

SPECT Imaging With Resolution Recovery

SPECT Imaging With Resolution Recovery

引用

2nd International conference on Advancements in Nuclear Instrumentation, Measurement Methods and their Applications

作者： Bronnikov, Andrei V. Bronnikov Algorithms NL-6800 AB Arnhem Netherlands

ISBN: (纸本)9781457709258

Single-photon emission computed tomography (SPECT) is a method of choice for imaging spatial distributions of radioisotopes. Applications of this method are found in medicine, biomedical research and nuclear industry. This paper deals with improving spatial resolution in SPECT by applying correction for the point-spread function (PSF) in the reconstruction algorithm and optimizing the collimator. Several approaches are considered: the use of a depth-dependent PSF model for a parallel-beam collimator derived from experimental data, the extension of this model to a fan-beam collimator, a triangular approximation of the PSF for reconstruction acceleration, and a method for optimal fan-beam collimator design. An unmatched projector/backprojector ordered subsets expectation maximization (OSEM) algorithm is used for image reconstruction. Experimental results with simulated and physical phantom data of a micro-SPECT system show a significant improvement of spatial resolution with the proposed methods.

关键词： image quality nuclear medicine single photon emission computed tomography (SPECT)

来源：评论

学校读者我要写书评

暂无评论

Which super-resolution algorithm is proper for Farsi text image sequences 2

Which super-resolution algorithm is proper for Farsi text im...

引用

2nd International conference on Pattern Recognition and image Analysis IPRIA

作者： Khodadadi, Elham Kanan, Hamidreza Rashidy Islamic Azad Univ Dept Elect Biomed & Mechatron Engn Qazvin Branch Qazvin Iran

ISBN: (纸本)9781479984459

In this paper we propose a new algorithm for super-resolution of Farsi text image sequences. Our algorithm contains three main steps as prior super-resolution algorithms;registration, reconstruction, and restoration. Due to special properties of Farsi texts such as appearance of dots in alphabet, selecting a proper super-resolution algorithm, especially in presence of noise, is more important. We propose an algorithm with an accurate sub-pixel registration and IBP reconstruction that reconstructs a high resolution image from a set of noisy low resolution observations. In restoration step we have exploited NLM algorithm to overcome image noise. We test our algorithm on synthetic and real data. Both quantitative and qualitative results show outperformance of our algorithm.

关键词： text super-resolution sub-pixel registration Iterative Back Projection NLM

来源：评论

学校读者我要写书评

暂无评论

Multi-frame blind deconvolution and bispectrum processing of atmospherically-degraded data: a comparison

Multi-frame blind deconvolution and bispectrum processing of...

引用

2nd conference on image reconstruction from incomplete data

作者： Matson, CL Schulze, KJ Billings, P Tyler, DW Directed Energy Directorate/Air Force Research Lab. (United States) KJS Consulting (United States) Textron Systems Corp. (United States) Univ. of New Mexico (United States)

ISBN: (纸本)0819445592

We analyze the quality of reconstructions obtained when using the multi-frame blind deconvolution (MFBD) algorithm and the bispectrum algorithm to reconstruct images from atmospherically-degraded data that are corrupted by detector noise. In particular, the quality of reconstructions is analyzed in terms of the fidelity of the estimated Fourier phase spectra. Both the biases and the mean square phase errors of the Fourier spectra estimates are calculated and analyzed. The reason that the comparison is made by looking at the Fourier phase spectra is because both the MFBD and bispectrum algorithms can estimate Fourier phase information from the image data itself without requiring knowledge of the system transfer function, and because Fourier phase plays a dominant role in image quality. Computer-simulated data is used for the comparison in order to be able to calculate true biases and mean square errors in the estimated Fourier phase spectra. For the parameters in this study, the bispectrum algorithm produced less-biased phase estimates in all cases than the MFBD algorithm. The MFBD algorithm produced mean square phase errors comparable to or lower than the bispectrum algorithm for good seeing and few data frames, while the converse is true for many data frames and poor seeing.

关键词： speckle imaging multi-frame blind deconvolution MFBD bispectrum

来源：评论

学校读者我要写书评

暂无评论

Application of Dictionary Learning in Compressed Sensing of data in MRI 2

Application of Dictionary Learning in Compressed Sensing of ...

引用

2nd International conference on Circuits, Controls, and Communications (CCUBE)

作者： Padole, Himanshu Joshi, S. D. Indian Inst Technol Dept Elect Engn Delhi India

ISBN: (纸本)9781538606155

In recent years, it is now well established that for the data like MRI images that admit the sparse representation in some transformed domain, Compressed Sensing (CS) approach is well suited for the accurate restoration tasks. Various analytical sparsifying transforms such as wavelets, finite differences and curvelets are used extensively in many CS methods. In this paper, a general framework for the adaptive learning of the sparsifying transform (dictionary) and reconstruction of the MR image from undersampled k-space data simultaneously is proposed. Here, we also propose the supervised dictionary learning framework adapted to specific task of MR image reconstruction and an efficient algorithm to solve the corresponding optimization problem. In this framework, overlapping image patches are used to exploit the local structure in the image to enforce the sparsity. Dictionary is trained using training images corresponding to particular class the given image belongs to. This results in better sparsities hence the higher undersampling rate. In this alternating reconstruction algorithm, firstly the sparsifying dictionary is learnt to remove aliasing effect and then restoring and filling of the k-space data is performed in the other step. Experiments are conducted on the brain MR image data set with different sampling methods. Results of these experiments show the improvement of around 2.5 dB in PSNR and improvement of around 0.1 in the HFEN value of the reconstructed image. Performance with various sampling schemes is evaluated and the results show that 2D variable density random undersampling scheme is best suited for the MRI application.

关键词： MRI dictionary learning compressed sensing sampling trajectories supervised learning sparse representation LARS LASSO

来源：评论

学校读者我要写书评

暂无评论

A New Secret image Sharing Scheme Based on Compressed Sensing 2

A New Secret Image Sharing Scheme Based on Compressed Sensin...

引用

2nd IEEE International conference on Cloud Computing and Big data Analysis (ICCCBDA)

作者： Yang, Fuqiang Dang, Na Zhang, Junxing Inner Mongolia Univ Sch Comp Sci Hohhot Peoples R China

ISBN: (纸本)9781509044993

In traditional secret image sharing schemes, all the data of a secret image have to be processed, which prolongs the algorithm execution. Meanwhile, the inflated data become a burden for network transmission and disk storage when many secret images need to be routinely shared. Compressed sensing technology measures the original image perceptually through a proper measurement matrix, and the measured data cover the vast majority of the useful information of the original image. While ensuring precise reconstruction, the original image is compressed from high dimensional to low dimensional and the amount of image data decreases dramatically. Thus, a number of problems caused by the large amount of data in traditional secret image sharing schemes could be solved by compressed sensing. In this paper, we combine the traditional secret image sharing with compressed sensing technology and show through experiments that the proposed method can clearly reduce the amount of data need to be processed and effectively shorten the algorithm execution time. The experimental results reveal that our method can shorten the image sharing time by 2.7% to 57.3% and the image restoration time by 3.3% to 57.7% under different compression ratios.

关键词： secret image sharing compressed sensing reconstruction algorithm

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：