检索结果-内蒙古大学图书馆

Wavelet spectrum analysis of EIT/SOHO images

SOLAR PHYSICS 2005年第1-2期228卷 301-321页

作者： Delouille, V De Patoul, J Hochedez, JF Jacques, L Antoine, JP Royal Observ Belgium B-1180 Brussels Belgium Univ Catholique Louvain Inst Theoret Phys B-1348 Louvain Belgium

The extreme ultraviolet imaging telescope (EIT) of SOHO offers a unique record of the solar atmosphere for its sampling in temperature, field of view, resolution, duration, and cadence. To investigate globally and locally its topology and evolution during the solar cycle, we consider a multi-scale approach, and more precisely we use the wavelet spectrum. We present three results among the applications of such a procedure. First, we estimate the typical dimension of the supergranules as seen in the 30.4 nm passband, and we show that the evolution of the characteristic network scale is almost in phase with the solar cycle. Second, we build pertinent time series that give the evolution of the signal energy present in the corona at different scales. We propose a method that detects eruptions and post-flaring activity in EUV image sequences. Third, we introduce a new way to extract active regions in EIT images, with perspectives in, e.g., long-term irradiance analysis.

关键词： SOLAR atmosphere image processing wavelets (Mathematics) SOLAR telescopes SOLAR activity

来源：评论

学校读者我要写书评

暂无评论

image ENHANCEMENT USING SGW SUPERRESOLUTION AND ITERATIVE BLIND DECONVOLUTION

IMAGE ENHANCEMENT USING SGW SUPERRESOLUTION AND ITERATIVE BL...

引用

作者： Chappalli, Mahesh B. PennState University Libraries

学位级别：Doctor of Philosophy

The field of superresolution has seen a tremendous growth in interest over the pastdecade. High resolution images are crucial in several applications including medicalimaging and diagnosis, military surveillance, satellite and astronomical imaging, andremote sensing. Constraints due to factors such as technology, cost, size, weight, andquality prevent the use of sensors with the desired resolution in image capture devicesand consequently, necessitate the design of superresolution algorithms to achieve thedesired image *** have emerged as a powerful tool in signal processing and many other *** generation wavelets were recently introduced and their flexibility and versatilityhas resulted in an ever-growing number of applications. They have been used in fieldsranging from the solution of partial differential equations to mesh refinement and modeling in computer graphics. Two prominent properties of second generation wavelets,viz. the ability to handle irregular sampling structures and the adaptation to arbitraryboundaries, which are at the heart of image sequence superresolution, motivated thisresearch on superresolution algorithms based on second generation wavelets. The developedtechniques also achieve simultaneous noise filtering by thresholding the computedwavelet coefficients prior to reconstruction. Analysis leading to the selection of a thresholdthat yields an optimal trade-off between noise reduction and blur introduction due to thresholding is subsequently presented. Since the choice of prediction neighborhoodin second generation wavelet transforms influences reconstructed image quality, an adaptive neighborhood based on approximated gradients is proposed to enhance the qualityof edges in the reconstructed images. Simulation results that demonstrate the superiorperformance of the developed techniques are also *** addition to noise, blur commonly affects the quality of the captured images/***, a deblurring module is

关键词： superresolution second generation wavelets blind deconvolution optimal thresholding blur support determination

来源：评论

学校读者我要写书评

暂无评论

Edge detection: wavelets versus conventional methods on DSP processors

引用

Machine Graphics and Vision 2005年第1期14卷 83-101页

作者： Abdel-Qader, Ikhlas M. Maddix, Marie E. Electrical and Computer Engineering Department College of Engineering and Applied Sciences Western Michigan University Kalamazoo MI 49008 ECE Department WMU Center College of Engineering and Applied Sciences Western Michigan University IEEE Accoustics Speech and Signal Processing Society IEEE Engineering in Medicine and Biology Society Society of Women Engineers Honor Society of Phi Kappa Phi Sigma Xi Scientific Research Society Tau Beta Pi Engineering Honors Fraternity Eaton Corporation Current Product Engineering Group

Edge detection is a cornerstone in any computer, robotic or machine vision system. Real time edge detection is a pre-process to many critical applications, such as assembly line inspection and surveillance. wavelets-based algorithms are replacing traditional algorithms, especially the Haar wavelet because of its simplicity. The Haar algorithm uses a multilevel decomposition to produce image edges corresponding to high frequency wavelet coefficients. In this paper, a real time edge detection algorithm based on Haar is analyzed and compared to conventional edge detectors. Other implemented and compared algorithms are the traditional Prewitt algorithm, and, from a newer generation, the Canny algorithm. The real time implementation of all algorithms is accomplished using TI TMS320C6711 card. In case of Haar, the multilevel decomposition improves the results obtained with noisy images. The results show that the Haar-based edge detector has a low execution time with accurate edge results, and thus represents a suitable algorithm for on-line vision system applications. Canny has produced the thinnest edges, but is not suitable for real time processing using the 6711, and falls short in edge results compared to the Haar results. The wavelet-based algorithm has outperformed other edge detectors.

关键词： Edge detection

来源：评论

学校读者我要写书评

暂无评论

Optical broadcast neural network architecture for vision applications

Optical broadcast neural network architecture for vision app...

引用

Conference on Independent Component Analyses, wavelets, Unsupervised Smart Sensors, and Neural Networks III

作者： Lamela, H Ruiz-Llata, M Cambre, DM Univ Carlos III Madrid Dept Tecnol Elect Leganes 28911 Madrid Spain

ISBN: (纸本)0819458031

In this paper we describe the implementation of a vision system based on an optoelectronic neural network architecture which is based on an optical broadcast interconnection scheme. The architecture of the neural network processor has been designed to exploit the computational characteristics of electronics and the communication characteristics of optics, thus it is based on an optical broadcast of input signals to a dense array of processing elements. In the proposed vision system, a CMOS sensor capture the image of an object, the output of the camera is introduced to the optoelectronic processor which compares the input image with a set of reference patterns, the optoelectronic processor provides the reference pattern that best match with the input image. The processing core of the system is an optoelectronic architecture that has been configured as a Hamming neural network.

关键词： Neural networks Optoelectronics image processing image sensors image classification Prototyping CMOS sensors Optical engineering Independent component analysis wavelets

来源：评论

学校读者我要写书评

暂无评论

image fusion method based on nonseparable wavelets

引用

MACHINE VISION AND applications 2005年第3期16卷 189-196页

作者： Liu, B Peng, Jx Hubei Univ Sch Math & Comp Sci Wuhan 430062 Peoples R China Huazhong Univ Sci & Technol Inst Image Recognit & Artificial Intelligence Wuhan 430074 Peoples R China

This paper presents an image fusion method based on a new class of wavelet - nonseparable wavelet with compact support, linear phase, orthogonality, and dilation matrix ((2)(0)(0)(2) ). We first construct a 6 x 6 nonseparable wavelet. filter bank. Using these filters the images involved are decomposed into nonseparable wavelet pyramids. Then the following fusion algorithm is proposed: for the low-frequency part, we select the average of the low-frequency subimages from both sensors. For every high-frequency subimage of each level, we select the absolute value of each pixel of the high-frequency subimage to form a new subimage, and the variance of each image patch over a 3 x 3 window in the new subimages is computed as an activity measurement. If the variance of the 3 x 3 window in one new subimage is greater than the variance of the corresponding 3 x 3 window in the other new subimage, then the center pixel value of the 3 x 3 window is selected as a new pixel value of the fused image. A new fused image is then reconstructed. The performance of the method is evaluated using entropy, root mean square error, and peak-to-peak signal-to-noise ratio. The experimental results show that this method has good vision effect. Because the nonseparable wavelet transform can extract more details from source images, all the features in the source images can be seen in the fused image, and the fused image can extract more information from the source images.

关键词： nonseparable wavelet image fusion variance

来源：评论

学校读者我要写书评

暂无评论

Complex wavelets versus gabor wavelets for facial feature extraction: A comparative study

Complex wavelets versus gabor wavelets for facial feature ex...

引用

Proceedings of SPIE-IS and T Electronic Imaging - image processing: Algorithms and Systems IV

作者： Sankaran, Harish Essaky Gotchev, Atanas Egiazarian, Karen Astola, Jaakko Institute of Signal Processing Tampere University of Technology P.O.Box 553 FIN-33101 Tampere Finland

In this paper two complex wavelet transforms, namely the Gabor wavelet transform and Kingsbury's Dual-Tree Complex wavelet transform (DT-CWT) are compared for their capabilities to extract facial features. The Gabor wavelets extract directional features from images and find frequent applications in computer vision problems of face detection and face recognition. The transform involves convolving an image with an ensemble of Gabor kernels, scale and directionally parameterized. As a result, a redundant image representation is obtained, where the number of transformed images is equal to the number of Gabor kernels used. However, repetitive convolution with 2-D Gabor kernels is a rather slow computational operation. The DT-CWT is a recently suggested transform, which provides good directional selectivity in six different fixed orientations at dyadic scales with the ability to distinguish positive and negative frequencies. It has a limited redundancy of four for images and is much faster than the Gabor transform to compute. Therefore, it arises as a good candidate to replace Gabor transform in applications, where the speed (i.e. on-line implementation) is a critical issue. We involve the two wavelet families in facial landmarks detection and compare their performance by statistical tests, e.g. by building Receiver Operating Characteristic (ROC) curves and by measuring the sensitivity of a particular feature extractor. We also compare results of Bayesian classification for the two families of feature extractors involved. © 2005 SPIE and IS&T.

关键词： Wavelet transforms

来源：评论

学校读者我要写书评

暂无评论

wavelets meet genetic imaging

Wavelets meet genetic imaging

引用

wavelets xI

作者： Wang, Yu-Ping School of Computing and Engineering Univ. of Missouri Kansas city MO

Genetic image analysis is an interdisciplinary area, which combines microscope image processing techniques with the use of biochemical probes for the detection of genetic aberrations responsible for cancers and genetic diseases. Recent years have witnessed parallel and significant progress in both image processing and genetics. On one hand, revolutionary multiscale wavelet techniques have been developed in signal processing and applied mathematics in the last decade, providing sophisticated tools for genetic image analysis. On the other hand, reaping the fruit of genome sequencing, high resolution genetic probes have been developed to facilitate accurate detection of subtle and cryptic genetic aberrations. In the meantime, however, they bring about computational challenges for image analysis. In this paper, we review the fruitful interaction between wavelets and genetic imaging. We show how wavelets offer a perfect tool to address a variety of chromosome image analysis problems. In fact, the same word "subband" has been used in the nomenclature of cytogenetics to describe the multiresolution banding structure of the chromosome, even before its appearance in the wavelet literature. The application of wavelets to chromosome analysis holds great promise in addressing several computational challenges in genetics. A variety of real world examples such as the chromosome image enhancement, compression, registration and classification will be demonstrated. These examples are drawn from fluorescence in situ hybridization (FISH) and microarray (gene chip) imaging experiments, which indicate the impact of wavelets on the diagnosis, treatments and prognosis of cancers and genetic diseases.

关键词： Imaging techniques

来源：评论

学校读者我要写书评

暂无评论

image enhancement using SGW superresolution and iterative blind deconvolution

Image enhancement using SGW superresolution and iterative bl...

引用

作者： Chappalli, Mahesh B. The Pennsylvania State University

学位级别：Ph.D.

The field of superresolution has seen a tremendous growth in interest over the past decade. High resolution images are crucial in several applications including medical imaging and diagnosis, military surveillance, satellite and astronomical imaging, and remote sensing. Constraints due to factors such as technology, cost, size, weight, and quality prevent the use of sensors with the desired resolution in image capture devices and consequently, necessitate the design of superresolution algorithms to achieve the desired image resolution. wavelets have emerged as a powerful tool in signal processing and many other fields. Second generation wavelets were recently introduced and their flexibility and versatility has resulted in an ever-growing number of applications. They have been used in fields ranging from the solution of partial differential equations to mesh refinement and modeling in computer graphics. Two prominent properties of second generation wavelets, viz. the ability to handle irregular sampling structures and the adaptation to arbitrary boundaries, which are at the heart of image sequence superresolution, motivated this research on superresolution algorithms based on second generation wavelets. The developed techniques also achieve simultaneous noise filtering by thresholding the computed wavelet coefficients prior to reconstruction. Analysis leading to the selection of a threshold that yields an optimal trade-off between noise reduction and blur introduction clue to thresholding is subsequently presented. Since the choice of prediction neighborhood in second generation wavelet transforms influences reconstructed image quality, an adaptive neighborhood based on approximated gradients is proposed to enhance the quality of edges in the reconstructed images. Simulation results that demonstrate the superior performance of the developed techniques are also included. In addition to noise, blur commonly affects the quality of the captured images/video. Typically,

关键词：

来源：评论

学校读者我要写书评

暂无评论

Multi-dictionary matching pursuit for servo error analysis applied to iterative learning control

Multi-dictionary matching pursuit for servo error analysis a...

引用

IEEE International Workshop on Intelligent signal processing (WISP)

作者： Rotariu, I Vullings, E Univ Sydney ARC Ctr Excellence Autonomous Syst Sydney NSW 2006 Australia

ISBN: (纸本)078039030X

wavelets and associated multiresolution analysis has had a major impact on signal processing, data compression, computer vision, telecommunication and a variety of other engineering and scientific disciplines. However, all of the aforementioned applications are limited to either wavelet analysis or wavelet characterization. The use of wavelets as basis in the direct control of the system dynamics has not been exploited [1]. In this paper we show how we can better control the time-varying nonlinear behavior of a motion system, i.e. a wafer stage apparatus, by integrating an adaptive Iterative Learning Control (ILC) technique with the time-frequency analysis of the servo error when acceleration feed-forward is applied. The performance of the presented learning control technique relies on an accurate identification of time-varying nonlinear and stochastic effects present in the servo error signal. The identification of these effects is performed by means of time-frequency analysis of the servo error and therefore, our goal is to obtain a high-resolution time-frequency energy distribution of the analyzed signal. In this paper we present a comparative analysis of the servo error energy density by four means: Wigner distribution;piecewise-linear Wigner distribution;adaptive signal decomposition over one dictionary of modulated versions of orthonormal bases of compactly supported wavelets having a fixed number of vanishing moments (which we call simple atomic dictionary);and by means of combining several simple atomic dictionaries into a complex atomic dictionary. We show that the latter approach leads to an improved time-frequency energy distribution.

关键词： atomic decomposition compactly supported wavelets dictionary Iterative Learning Control orthonormal bases Wigner distribution

来源：评论

学校读者我要写书评

暂无评论

Efficiency analysis for a mixed-signal focal plane processing architecture

引用

Journal of VLSI signal processing Systems for signal, image, and Video Technology 2005年第1期41卷 65-80页

作者： Robinson, William H. Wills, D. Scott Laboratory Georgia Institute of Technology School of Electrical and Computer Engineering Atlanta GA 30332-0250 United States Department of Electrical Engineering and Computer Science Vanderbilt University

Monolithic integration of photodetectors, analog-to-digital converters, data storage, and digital processing can improve both the performance and the efficiency of future portable image products. However, digitizing and processing a pixel at the detection site presents the design challenge to deliver a system with the required performance at the lowest cost, not just a system with the highest performance. This paper analyzes the area-time efficiency, the area efficiency, and the energy efficiency of a mixed-signal, SIMD focal plane processing architecture that executes front-end image applications with neighborhood processing. Implementations of the focal plane architecture achieve up to 81x higher area efficiency and up to 11x higher energy efficiency when compared to traditional TI DSP chips. Higher efficiency ratings are required to maintain portability while addressing technology limitations such as interconnect wiring density, heat extraction, and battery life. Systems can be implemented with a less expensive fabrication technology by increasing the number of pixels per processing element (PPE). © 2005 Springer Science + Business Media, Inc.

关键词： Digital signal processing

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：