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PNoC: a flexible circuit-switched NoC for FPGA-based systems

IEE PROCEEDINGS-COMPUTERS AND DIGITAL TECHNIQUES 2006年第3期153卷 181-188页

作者： Hilton, C. Nelson, B. Rincon Res Corp Tucson AZ 85711 USA Brigham Young Univ Provo UT 84602 USA

Increases in chip density due to Moore's law allow for the implementation of ever larger and more complex systems on a single chip (SoCs). The communication mechanisms employed in such SoCs are an important contribution to their overall performance. Networks on chip (NoCs) promise to overcome the scalability problems found in bus-based interconnect. To date, most work has focused on packet-switched NoCs. Circuit-switched networks are an intriguing alternative, which promise high communication rates and predictable communication latencies. A new lightweight circuit-switched architecture called programmable NoC (PNoC) is described. PNoC is a flexible architecture that is suitable for use in FPGA-based systems. Implementation results on a Virtex-II Pro device are given using an image binarisation demonstration which resulted in as much as a 23 x speedup compared with a shared bus implementation.

关键词： programmable NoC flexible circuit switch architecture Digital signal processing chips Logic and switching circuits image binarisation communication mechanism scalability problem network-on-chip SoC communication latency rate Moores law network on chip Computer vision and image processing techniques bus interconnect Logic circuits field programmable gate arrays circuit switching Optical, image and video signal processing image processing complex system field programmable gate array packet switch circuit switched architecture FPGA system Microprocessors and microcomputers chip density system on chip digital signal processing chips

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Scalable phase extraction methods for phase plane motion estimation

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IEE PROCEEDINGS-VISION image AND signal processing 2006年第6期153卷 860-868页

作者： Molino, A. Vacca, F. Masera, G. Nguyen, T. Q. Politecn Torino Dipartimento Elettr I-10129 Turin Italy Univ Calif San Diego Dept Elect & Comp Engn La Jolla CA 93093 USA

To efficiently compute the phase difference (PD) between two complex numbers, two novel approaches are described. The problem of fast PD computation is central in many applications. As a case study, the main focus is on the phase correlation technique that is used for motion estimation. Starting from the problem statement, the system requirements are dealt with showing how PD requires a remarkable amount of computational resources. Reduced complexity techniques are then proposed and specifically tailored to suit the application needs. Each solution is completely implemented both in 0.25 mu m as well as 0.13 mu m CMOS. The so-called LUT-ROT exhibits noteworthy figures in terms of area occupation, delay and power dissipation, saving nearly 50% in terms of area and power when compared to recent work on this subject.

关键词： CMOS phase difference feature extraction power dissipation phase plane motion estimation Computational complexity computational complexity scalable phase extraction methods fast PD computation motion estimation Optical, image and video signal processing phase correlation technique reduced complexity techniques Computer vision and image processing techniques LUT-ROT

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Multiresolution phase retrieval in the Fresnel region by use of wavelet transform

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JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS image SCIENCE AND VISION 2006年第2期23卷 279-287页

作者： Souvorov, A Ishikawa, T Kuyumchyan, A JASRI SPring 8 Mikazuki Hyogo 6795198 Japan Russian Acad Sci Inst Microelect Technol & High Pur Mat Chernogolovka 142432 Russia

A multiresolution (multiscale) analysis based on wavelet transform is applied to the problem of optical phase retrieval from the intensity measured in the in-line geometry (lens-free). The transport-of-intensity equation and the Fresnel diffraction integral are approximated in terms of a wavelet basis. A solution to the phase retrieval problem can be efficiently found in both cases using the multiresolution concept. Due to the hierarchical nature of wavelet spaces, wavelets are well suited to multiresolution methods that contain multigrid algorithms. Appropriate wavelet bases for the best solution approximation are discussed. The proposed approach reduces the computational complexity and accelerates the convergence of the solution. It is robust and reliable, and successful on both simulated and experimental images obtained with hard x rays. (c) 2006 Optical Society of America.

关键词： Fresnel diffraction Fresnel equations Hard x rays Phase retrieval signal processing Wavelet transforms

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Bayesian wavelet-based methods for the detection of multiple changes of the long memory parameter

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IEEE TRANSACTIONS ON signal processing 2006年第11期54卷 4461-4470页

作者： Ko, Kyungduk Vannucci, Marina Boise State Univ Dept Math Boise ID 83725 USA Texas A&M Univ Dept Stat College Stn TX 77843 USA

Long memory processes are widely used in many scientific fields, such as economics, physics, and engineering. Change point detection problems have received considerable attention in the literature because of their wide range of possible applications. Here we describe a wavelet-based Bayesian procedure for the estimation and location of multiple change points in the long memory parameter of Gaussian autoregressive fractionally integrated moving average models (ARFIMA(p, d, q)), with unknown autoregressive and moving average parameters. Our methodology allows the number of change points to be unknown. The reversible jump Markov chain Monte Carlo algorithm is used for posterior inference. The method also produces estimates of all model parameters. Performances are evaluated on simulated data and on the benchmark Nile river dataset.

关键词： ARFIMA models Bayesian inference change point reversible jump wavelets

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Noise reduction from magnetic resonance images using nonseperable transforms - art. no. 61446F

Noise reduction from magnetic resonance images using nonsepe...

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Medical Imaging 2006 Conference

作者： Nezhadarya, Ehsan Shamsollahi, Mohammad Bagher Sharif Univ Technol Dept Elect Engn Tehran Iran

ISBN: (纸本)0819464236

Multi-scale transforms have got a lot of applications in image processing, in recent years. Wavelet transform is a powerful multiscale transform for denoising noisy signals and images, but the usual two-dimensional separable wavelets are sub-optimal. These separable wavelet transforms can successfully identify zero dimensional singularities in images, but can weakly identify one dimensional singularities such as edges, curves and lines. In this sense, non-separable transforms such as Ridgelet and Curvelet transforms are proposed by Candes and Donoho. The coefficients produced by these non-separable transforms have shown to be sparser than wavelet coefficients. This fact results in better denoising capabilities than wavelet transform. These new non-separable transforms can identify direction in lines and curves, because of special structure of their basis elements. Basically, Magnetic Resonance images are probable to have Rician noise. In some special cases, this kind of noise can be supposed to be white Gaussian noise. In this paper, a new method for denoising MR images is proposed. This method is based on Monoscale Ridgelet transform. It is shown that this transform can successfully denoise MR images embedded in white Gaussian noise. The results are better in comparison with usual wavelet denoising methods, based on both visual perception and signal-to-noise ratio.

关键词： image denoising multiresolution and wavelets magnetic resonance Imaging ridgelet transform

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A taxonomy of color image filtering and enhancement solutions

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ADVANCES IN IMAGING AND ELECTRON PHYSICS, VOL 140 2006年 140卷 187-264页

作者： Lukac, Rastislav Plataniotis, Konstantinos N. Univ Toronto Multimedia Lab Edward S Rogers Sr Dept ECE Toronto ON M5S 3G4 Canada

The purpose of this chapter is to present the state-of-the-art in color image filtering and enhancement techniques, and to discuss in a systematic and comprehensive way the most important developments in the field of color image filtering. The perception of color is of paramount importance since human observers routinely use color information to sense the environment, recognize semantic objects of interest, and convey information about the environment. Color image processing is concerned with the manipulation of digital color images on electronic devices, such as computers and digital cameras, through the utilization of digital signal processing methods. Digital image processing, a well-established research discipline with many important practical applications, focuses on the conversion of a continuous image field into an equivalent digital form. The synthesis of images from the signals arising from various sensor systems is accomplished by a digital process directed to transforming the signal into a form allowing visual or machine perception. The requirements for an ideal conversion system are usually expressed in terms of certain technical properties, such as the resolution of the imaging systems, photometric accuracy, quantization levels, intensity of intrinsic noise, and many others. In this chapter Section II reviews briefly the fundamentals of the trichromatic theory of color representation emphasizing the connections between colorimetric properties and vectorial representation in a three-dimensional (3D) color space. This part also includes Section III in which synthetic color image noise models are reviewed. The purpose is to provide insights into the fundamentals of color image formation and a basic understanding of the objectives behind the development of the various color image filtering schemes. The analysis of the image noise in digital image acquisition systems often focuses on random noise sources, such as those associated with quantum signal detectio

关键词： Product development

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Lighting inhomogeneities removal by wavelet analysis

Lighting inhomogeneities removal by wavelet analysis

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Conference on Wavelet applications in Industrial processing IV

作者： Laligant, O. Meriaudeau, F. Truchetet, F. CNRS Le2i UMR 5158 12 Rue Fonderie Le Creusot France

ISBN: (纸本)9780819464811

Lighting uniformity is always an issue in visual inspection of industrial parts. While the human visual system is quite able to cope with this kind of problem, artificial vision systems are subject to false and no detection rate increase when the lighting conditions are not well mastered. If many authors have proposed various methods to unbiase image, most of the time they are designed in an "ad hoc" way and they are very dependent on the experimental conditions. It can be shown that a large class of the inhomogeneities in images due to lighting conditions can be reasonably modelled by a polynomial dependency of the luminance. The wavelet analysis theory proposes a lot of bases with various number of vanishing moments. By keeping only some wavelet coeffcients it is possible to reconstruct an unbiased signal in which the interesting features, characterized by there resolution pertinence range, are cleaned from the polynomial variations supposed to be due to inhomogeneous lighting conditions. In this paper, after a brief presentation of a realistic lighting model, we show that the luminance image can be approximated by a polynomial function. Then we propose a method, based on a partial reconstruction after multiresolution analysis, allowing to remove approximately the polynomial component of the signal. Two variants are also proposed to improve the performance by either detecting more precisely the polynomial component, either limiting the error occurring when neglecting the approximation signal in the reconstruction process. A simulation in 1D and 2D illustrates these propositions. Some results obtained on examples of real artificial vision inspection problems are finally given.

关键词： artificial vision surface inspection lighting homogeneity wavelets vanishing moments wavelet filtering

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A total variation wavelet inpainting model with multilevel fitting parameters

A total variation wavelet inpainting model with multilevel f...

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Conference on Advanced signal processing Algorithms, Architectures, and Implementations xVI

作者： Chan, Tony F. Shen, Jianhong Zhou, Hao-Min Univ Calif Los Angeles Dept Math Los Angeles CA 90095 USA Univ Minnesota Dept Math Minneapolis MN 55455 USA Georgia Inst Technol Sch Math Atlanta GA 30332 USA

ISBN: (纸本)0819463922

In [14], we have proposed two total variation (TV) minimization wavelet models for the problem of filling in missing or damaged wavelet coefficients due to lossy image transmission or communication. The proposed models can have effective and automatic control over geometric features of the inpainted images including sharp edges, even in the presence of substantial loss of wavelet coefficients, including in the low frequencies. In this paper, we investigate a modification of the model for noisy images to further improve the recovery properties by using multi-level parameters in the fitting term. Some new numerical examples are also shown to illustrate the effectiveness of the recovery.

关键词： wavelets image compression image restoration image processing image quality Wavelet transforms Automatic control Cameras image transmission Mathematics

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A review of wavelet denoising in MRI and ultrasound brain imaging

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CURRENT MEDICAL IMAGING 2006年第2期2卷 247-260页

作者： Pizurica, Aleksandra Wink, Alle Meije Vansteenkiste, Ewout Philips, Wilfried Roerdink, Jos B. T. M. Univ Ghent Dept Telecommun & Informat Proc TELIN B-9000 Ghent Belgium Univ Cambridge Addenbrookes Hosp Dept Psychiat Brain Mapping Unit Cambridge CB2 2QQ England Univ Groningen Inst Math & Comp Sci NL-9700 AV Groningen Netherlands

There is a growing interest in using multiresolution noise filters in a variety of medical imaging applications. We review recent wavelet denoising techniques for medical ultrasound and for magnetic resonance images and discuss some of their potential applications in the clinical investigations of the brain. Our goal is to present and evaluate noise suppression methods based on both image processing and clinical expertise. We analyze two types of filters for magnetic resonance images (MRI): noise Suppression in magnitude MRI images and denoising blood oxygen level-dependent (BOLD) response in functional MRI images (fMRI). The noise distribution in magnitude MRI images is Rician, while the noise distribution in BOLD images has been recently shown to follow a Gaussian model well. We evaluate different methods based on signal to noise ratio improvement and based on the preservation of the shape of the activated regions in fMRI. A critical view on the problem of speckle filtering in ultrasound images is given where we discuss some of the issues that are overlooked in many speckle filters like the relevance of the "speckled texture", expert-defined features of interest and the reliability of the common speckle models. We analyze the use of multiresolution speckle filters to improve the automatic processing steps in the clinical research of non-cystic periventricular leukomalacia. In particular we apply speckle filters to ultrasound neonatal brain images and we evaluate the influence of the filtering on the effectiveness of the subsequent classification and segmentation of flares of affected tissue in comparison with the manual delineation of clinicians.

关键词： image denoising wavelets magnetic resonance imaging ultrasound statistical parametric mapping false discovery rate control

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Biorthogonal wavelets of maximum coding gain through pseudoframes for subspaces

Biorthogonal wavelets of maximum coding gain through pseudof...

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Conference on Mathematics of Data/image Pattern Recognition, Compression and Encryption with Application Ix

作者： Herman, Matthew A. Li, Shidong Univ Calif Davis Dept Math 1 Shields Ave Davis CA 95616 USA San Francisco State Univ Dept Math San Francisco CA 94132 USA

ISBN: (纸本)0819463949

A method for designing a signal-adapted, two-channel biorthogonal wavelet filter bank that maximizes coding gain is presented using the technique of Pseudoframes for Subspaces (PFFS). At the same time the PFFS model is able to incorporate the requirements of regularity and perfect reconstruction into this design. The coding gain achieved for AR(2) signals can result in a reduction in bit rate of more than 0.66 bits per sample as compared to traditional biorthogonal wavelet filter banks of the same length. The ability for PFFS to combine all of these design elements using an unconstrained optimization parameter makes pursuing this technique worthwhile.

关键词： subband coding gain biorthogonal wavelets signal-adapted filter banks pseudoframes frames

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