检索结果-内蒙古大学图书馆

Compressed Sensing MRI Reconstruction from Highly Undersampled k-Space Data Using Nonsubsampled Shearlet Transform Sparsity Prior

引用

MATHEMATICAL PROBLEMS IN ENGINEERING 2015年第1期2015卷 1-18页

作者： Yuan, Min Yang, Bingxin Ma, Yide Zhang, Jiuwen Zhang, Runpu Zhang, Caiyuan Lanzhou Univ Sch Informat Sci & Engn Lanzhou 730000 Peoples R China Shanghai Jiao Tong Univ Sch Med Xinhua Hosp Dept Radiol Shanghai 200092 Peoples R China

Compressed sensing has shown great potential in speeding up MR imaging by undersampling k-space data. Generally sparsity is used as a priori knowledge to improve the quality of reconstructed image. Compressed sensing MR image (CS-MRI) reconstruction methods have employed widely used sparsifying transforms such as wavelet or total variation, which are not preeminent in dealing with MR images containing distributed discontinuities and cannot provide a sufficient sparse representation and the decomposition at any direction. In this paper, we propose a novel CS-MRI reconstruction method from highly undersampled k-space data using nonsubsampled shearlet transform (NSST) sparsity prior. In particular, we have implemented a flexible decomposition with an arbitrary even number of directional subbands at each level using NSST for MR images. The highly directional sensitivity of NSST and its optimal approximation properties lead to improvement in CS-MRI reconstruction applications. The experimental results demonstrate that the proposed method results in the high quality reconstruction, which is highly effective at preserving the intrinsic anisotropic features of MRI meanwhile suppressing the artifacts and added noise. The objective evaluation indices outperform all compared CS-MRI methods. In summary, NSST with even number directional decomposition is very competitive in CS-MRI applications as sparsity prior in terms of performance and computational efficiency.

关键词： COMPRESSED sensing (signal processing) MAGNETIC resonance imaging image reconstruction K-spaces DECOMPOSITION (Mathematics) SENSITIVITY analysis

来源：评论

学校读者我要写书评

暂无评论

Multimedia signals and Systems: Basic and Advanced Algorithms for signal processing

引用

2015年

作者： Srdjan S Stanković Irena Orović Ervin Sejdić

ISBN: (纸本)9783319239484

This book is designed for students, professionals and researchers in the field of multimedia and related fields with a need to learn the basics of multimedia systems and signal processing. Emphasis is given to the analysis and processing of multimedia signals (audio, images, and video). Detailed insight into the most relevant mathematical apparatus and transformations used in multimedia signal processing is given. A unique relationship between different transformations is also included, opening new perspectives for defining novel transforms in specific applications. Special attention is dedicated to the compressive sensing area, which has a great potential to contribute to further improvement of modern multimedia systems. In addition to the theoretical concepts, various standard and more recently accepted algorithms for the reconstruction of different types of signals are considered. Additional information and details are also provided to enable a comprehensive analysis of audio and video compression algorithms. Finally, the book connects these principles to other important elements of multimedia systems, such as the analysis of optical media, digital watermarking, and telemedicine. New to this edition:Introduction of the generalization concept to consolidate the time-frequency signal analysis, wavelet transformation, and Hermite transformation Inclusion of prominent robust transformation theory used in the processing of noisy multimedia data as well as advanced multimedia data filtering approaches, including image filtering techniques for impulse noise environment Extended video compression algorithms Detailed coverage of compressive sensing in multimedia applications

关键词：

来源：评论

学校读者我要写书评

暂无评论

Secure Hybrid Robust Watermarking Technique for Medical images 4th

Secure Hybrid Robust Watermarking Technique for Medical Imag...

引用

4th International Conference on Eco-Friendly Computing and Communication Systems (ICECCS)

作者： Sharma, Abhilasha Singh, Amit Kumar Ghrera, S. P. Jaypee Univ Informat Technol Waknaghat Dept Comp Sci & Engn Solan Himachal Prades India

The protection of data is of at prime urgency in the medical field to boost the telemedicine applications. There is a need of robust and secure mechanism to transfer the medical images over the Internet. The proposed watermarking method is based on two popular transform domain techniques, discrete wavelet transforms (DWT) and discrete cosine transform (DCT). In the embedding process, the cover medical image is divided into two separate parts, region of interest (ROI) and non region of interest (NROI). For the identity authentication purpose, multiple watermarks in the form of image and text are embedding into ROI and NROI part of the same cover media object respectively. In order to enhance the security of the text watermark, Rivest-Shamir-Adleman (RSA) encryption technique is applied to the text watermark before embedding and the encrypted EPR data is embedded into the NROI portion of the cover medical image. The performance of the proposed method is evaluated for signal processing attacks and the desired outcome is obtained without significant degradation in extracted watermark and perceptual quality of the watermarked image. (C) 2015 The Authors. Published by Elsevier B.V.

关键词： DWT DCT medical image image and text watermarks RSA ROI and NROI

来源：评论

学校读者我要写书评

暂无评论

DCT Combined With Fractal Quadtree Decomposition and Huffman Coding for image Compression

DCT Combined With Fractal Quadtree Decomposition and Huffman...

引用

International Conference on Condition Assessment Techniques in Electrical Systems (CATCON)

作者： Padmavati, S. Mesharam, Vaibhar Jain Univ Dept Elect Engn Bangalore Karnataka India

ISBN: (纸本)9781467377485

With advancement of technology, the image processing techniques play an important role. image processing is required to improve the pictorial information for human perception and for autonomous machine applications. It finds application in various fields such as quality control, remote sensing, imaging science, etc. It also finds application in areas where efficient storage and transmission of images is necessary, Say for example;we want to store an image in the computer with less disk space. Also, in cases where we want to signal an image or video on a transmission medium with less bandwidth communication channel. images are usually in the form of matrices and an uncompressed image uses huge number of bytes for storage. image compression is used to reduce the size of the bitmap without compromising on the quality of an image. This enables to store large number of images in the same given amount of storage space. image compression will also reduce the time taken to transmit or to download images from the internet. Many methods are available to compress an image file. The image compression methods which have gained popularity are the transform based coding methods like Discrete Cosine Transform (DCT), discrete wavelet Transform (DWT) and fractals. However these methods have drawbacks like low compression ratio and high encoding time. In this paper a new hybrid methodology is proposed by combining lossy and lossless compression methods. The proposed hybrid technique combines DCT and fractal quadtree decomposition with Huffman encoding of threshold value 0.2. The results obtained from the proposed method are then compared with state-of-the-art compression methods.

关键词： image Compression DCT Fractal image Compression Huffman Coding Quadtree Decomposition

来源：评论

学校读者我要写书评

暂无评论

Dual tree complex wavelet transform based speech enhancement

Dual tree complex wavelet transform based speech enhancement

引用

IEEE signal processing and Communications applications (SIU)

作者： Hacı Taşmaz Elektrik-Elektronik Mühendisliği Bölümü Adıyaman Üniversitesi Mühendislik Fakültesi Türkiye

Dual tree complex wavelet transform (DT-CWT) has the advantages of nearly shift-invariance and directional selectivity (for two or more dimensions) over the classical discrete wavelet transform. These advantages are essential for many signal processing applications (i.e. image fusion, image enhancement, pattern recognition). In his study, a speech enhancement method based on the DT-CWT has been proposed in order to test its performance in speech enhancement. An efficient estimator, multiplicatively modified log-spectral amplitude (MM-LSA) estimator is used for the enhancement of noisy subband wavelet coefficients. The objective and experimental results show the superiority of the proposed method to the wavelet transform based methods well known in the literature.

关键词： Speech enhancement Discrete wavelet transforms wavelet packets Speech

来源：评论

学校读者我要写书评

暂无评论

A novel approach for image compression based on multi-level image thresholding using discrete wavelet transform and cricket algorithm

A novel approach for image compression based on multi-level ...

引用

IEEE signal processing and Communications applications (SIU)

作者： Murat Canayaz Ali Karci Bilgisayar Bilimleri Araştırma ve Uygulama Merkezi Yüzüncü Yıl Üniversitesi Van Türkiye Bilgisayar Mühendisliği Bölümü İnönü Üniversitesi Malatya Türkiye

applications of image compression is important in terms of time and resource management considering factors such as require more time to send according to the size of image over the network and large amount of space is high dimensional data for storing images. In this study, a new approach can be using at image compression process will be introduced. Firstly, image subjected to discrete wavelet transform for extracting feature. Then multi-level threshold values will be find with Shanon entropy in the obtained image. The maximum value of objective function will be obtained with the help of cricket algorithm at the threshold values finding step. This algorithm is a meta-heuristic algorithm that based on population. The threshold values that obtained through algorithm using to compressing the images will be provided. At the end of the study, the image compression ratio, the proposed approach running on a standard test image will be given.

关键词： image coding Discrete wavelet transforms Entropy Feature extraction PSNR signal processing algorithms

来源：评论

学校读者我要写书评

暂无评论

Characterizing Point Spread Function (PSF) fluctuations to improve Resident Space Object (RSO) detection 8

Characterizing Point Spread Function (PSF) fluctuations to i...

引用

Conference on Sensors and Systems for Space applications

作者： Hardy, Tyler J. Cain, Stephen C. Air Force Inst Technol Dayton OH 45433 USA

ISBN: (纸本)9781628415858

This research paper deals with methods for improving the performance of Electro-optical detection systems designed to find Resident Space Objects (RSOs). Some methods for detecting RSOs rely on accurate knowledge of the system Point Spread Function (PSF). The PSF is a function of the telescope optics, the atmosphere, and other factors including object intensity and noise present in the system. Due to the random photon arrival times, any observed data will contain Poisson noise. Assuming that other noise sources such as dark current and readout noise do not contribute significantly, the final source of intensity fluctuations in the data is the atmosphere. To quantify these fluctuations, an optical model of a telescope system is developed, and its PSF is simulated. In a long exposure image, the effects of the atmosphere are well characterized with the long exposure atmosphere Optical Transfer Function (OTF). In contrast, a short exposure image does not average the fluctuations as effectively. To model the atmosphere, random phase screens with Kolmogorov statistics are added to the optical model to observe PSF fluctuations in short exposure telescope data. The distribution of the peak intensity is analyzed for varying exposure times and atmospheric turbulence strengths. This distribution is combined with the Poisson random arrival times of photons to create a combined model for received data, which is then used to design a new detection algorithm. The performance of the new space object detection algorithm will be compared to a traditional algorithm using simulated telescope data.

关键词： Space Object Detection Remote Sensing Telescope signal processing Intensity Fluctuations

来源：评论

学校读者我要写书评

暂无评论

基于ROAD和小波收缩的MLEM低剂量CT重建算法

引用

计算机应用与软件 2016年第2期33卷 156-160,178页

作者：董婵婵桂志国张权郝慧艳张芳刘祎孙未雅中北大学信息与通讯工程学院山西太原030051

针对低剂量CT(Computed Tomography)重建图像质量退化的问题,提出一种基于小波收缩和绝对差值排序各项异性扩散的MLEM(Maximum Likelihood Expectation Maximization)低剂量CT重建算法。算法在每次迭代中首先采用MLEM算法对低剂量CT投... 详细信息

针对低剂量CT(Computed Tomography)重建图像质量退化的问题,提出一种基于小波收缩和绝对差值排序各项异性扩散的MLEM(Maximum Likelihood Expectation Maximization)低剂量CT重建算法。算法在每次迭代中首先采用MLEM算法对低剂量CT投影数据进行重建。由于各项异性扩散对噪声敏感,所以算法先对重建后的图像进行小波变换,再在更稳定的低频小波域进行基于绝对差值排序的各项异性扩散处理,对小波高频系数进行软阈值降噪处理。然后将降噪处理后的系数进行小波反变换,得到降噪后的图像。最后使用中值滤波对图像进行处理,从而消除脉冲噪声点。实验结果表明,与其他几种常用重建算法相比,该算法重建的图像信噪比更高,归一化均方误差更小,处理后的图像更清晰,即可以在抑制噪声的同时,较好地保持图像的边缘和细节信息。

关键词：低剂量CT 小波变换图像重建绝对差值排序各向异性扩散

来源：评论

学校读者我要写书评

暂无评论

Content based medical image classification using discrete wavelet and cosine transforms

Content based medical image classification using discrete wa...

引用

IEEE signal processing and Communications applications (SIU)

作者： Zehra Karhan Burhan Ergen Bilgisayar Mühendisliği Bölümü Ondokuz Mayıs Üniversitesi Samsun TÜRKÎYE Bilgisayar Mühendisliği Bölümü Fırat Üniversitesi Elazığ TÜRKÎYE

In this study, we aimed to determine whether the medical image belongs to that class or not, using the textural features of medical images. The study was performed on the images in IRMA (image Retrieval in Medical applications), the international database. After performing pre process on the our current medical images, discrete wavelet transform (DWT) was applied and then discrete cosine transform (DCT) was applied to each band components. After feature extraction, using of 1%, 3%, 5% and 7% of the obtained data were classified. K-Nearest neighbor algorithm (KNN) was used in the classification phase. The classification performance was around 87%.

关键词： Discrete wavelet transforms Discrete cosine transforms Biomedical imaging image retrieval Medical services Biomedical equipment

来源：评论

学校读者我要写书评

暂无评论

Identification of acrylamide in fried potato crisps using image processing in wavelet domain

Identification of acrylamide in fried potato crisps using im...

引用

International Conference on Telecommunications and signal processing (TSP)

作者： Anushikha Singh Malay Kishore Dutta Radim Burget Jan Masek Amity University NOIDA Uttar Pradesh India

Acrylamide is a toxic carcinogenic material that commonly occurs in heated starchy food items like potato crisps. Identification of such toxic chemical in food items using conventional chemical laboratory based methods is time consuming and expensive and may need specialized manpower for such laboratory testing. This paper proposes an efficient image processing based non-destructive testing method for identification of acrylamide in potato crisps. The image of the potato crisps is automatically segmented and features are extracted from the images in wavelet domain. These features are then analyzed for identification of the presence of acrylamide in these samples. The variation in the various features of the image is related to the presence of acrylamide. The experimental results indicate that the proposed method is efficient for identification of acrylamide from the wavelet features of the images. The proposed method achieves 90% of accuracy and it can be used for real time applications.

关键词： Feature extraction image segmentation image color analysis wavelet coefficients wavelet analysis

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：