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Efficient lifting wavelet transform for microprocessor and VLSI applications

IEEE signal processing LETTERS 2005年第2期12卷 120-122页

作者： Olkkonen, H Olkkonen, JT Pesola, P Univ Kuopio Dept Appl Phys FIN-70211 Kuopio Finland VTT Elect Oulu 90571 Finland Univ Kuopio AIV Inst Mol Sci Cognit Neurobiol Lab FIN-70211 Kuopio Finland

Recently, wavelet analysis has gained an established role in signal and image processing applications. In this paper, we present a discrete wavelet transform algorithm based on the lifting scheme. The Haar wavelet transformed and decimated signals are lifted by the ladder-type network. A unique lifting filter is designed for in-place computation. The present algorithm is especially suitable for microprosessor and VLSI applications since it can be implemented by integer arithmetics using only register shifts and summations.

关键词： lifting scheme microprocessors VLSI wavelet transform

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ON SAMPLING THEOREM, waveletS, AND wavelet TRANSFORMS

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IEEE TRANSACTIONS ON signal processing 1993年第12期41卷 3524-3535页

作者： XIA, XG ZHANG, Z Communication Sciences Institute Department of Electrical Engineering-Systems University of Southern California Los Angeles CA USA

The classical Shannon sampling theorem has resulted in many applications and generalizations. From a multiresolution point of view, it provides the sine scaling function. In this case, for a band-limited signal, its wavelet series transform (WST) coefficients below a certain resolution level can be exactly obtained from the samples with a sampling rate higher than the Nyquist rate. In this research, we study the properties of cardinal orthogonal scaling functions (COSF), which provide the standard sampling theorem in multiresolution spaces with scaling functions as interpolants. We show that COSF with compact support have and only have one possibility which is the Haar pulse. We present a family of COSF with exponential decay, which are generalizations of the Haar function. With these COSF, an application is the computation of WST coefficients of a signal by the Mallat algorithm. We present some numerical comparisons for different scaling functions to illustrate the advantage of COSF. For signals which are not in multiresolution spaces, we estimate the aliasing error in the sampling theorem by using uniform samples.

关键词： Sampling methods wavelet transforms signal resolution signal processing signal sampling Fourier transforms Computer applications image processing image sampling

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Discrete wavelet Transform and Data Expansion Reduction in Homomorphic Encrypted Domain

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IEEE TRANSACTIONS ON image processing 2013年第6期22卷 2455-2468页

作者： Zheng, Peijia Huang, Jiwu Sun Yat Sen Univ Sch Informat Sci & Technol Guangzhou 510006 Guangdong Peoples R China

signal processing in the encrypted domain is a new technology with the goal of protecting valuable signals from insecure signal processing. In this paper, we propose a method for implementing discrete wavelet transform (DWT) and multiresolution analysis (MRA) in homomorphic encrypted domain. We first suggest a framework for performing DWT and inverse DWT (IDWT) in the encrypted domain, then conduct an analysis of data expansion and quantization errors under the framework. To solve the problem of data expansion, which may be very important in practical applications, we present a method for reducing data expansion in the case that both DWT and IDWT are performed. With the proposed method, multilevel DWT/IDWT can be performed with less data expansion in homomorphic encrypted domain. We propose a new signal processing procedure, where the multiplicative inverse method is employed as the last step to limit the data expansion. Taking a 2-D Haar wavelet transform as an example, we conduct a few experiments to demonstrate the advantages of our method in secure image processing. We also provide computational complexity analyses and comparisons. To the best of our knowledge, there has been no report on the implementation of DWT and MRA in the encrypted domain.

关键词： Data expansion discrete wavelet transform (DWT) homomorphic encryption multiplicative inverse method (MIM) multiresolution analysis (MRA) secure signal processing signal processing in the encrypted domain

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Generalized Gaussian scale mixtures: A model for wavelet coefficients of natural images

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signal processing-image COMMUNICATION 2018年 66卷 87-94页

作者： Gupta, Praful Moorthy, Anush Krishna Soundararajan, Rajiv Bovik, Alan Conrad Univ Texas Austin Dept Elect & Comp Engn Austin TX 78712 USA Netflix Inc Los Angeles CA USA Indian Inst Sci Dept Elect Commun Engn Bangalore Karnataka India

We develop a Generalized Gaussian scale mixture (GGSM) model of the wavelet coefficients of natural and distorted images. The GGSM model, which is more general than and which subsumes the Gaussian scale mixture (GSM) model, is shown to be a better representation of the statistics of the wavelet coefficients of both natural as well as distorted images. We demonstrate the utility of the model by applying it to various image processing applications, including blind distortion identification and no reference image quality assessment (NR-IQA). Similar to the GSM model, the GGSM model is useful for motivating the use of local divisive energy normalization, especially when the wavelet coefficients are computed on distorted pictures. We show that the GGSM model can lead to improved performance in distortion-related applications, while providing a more principled approach to the statistical processing of distorted image signals. The software release of a GGSM-based NR-IQA approach called DIIviNE-GGSM is available online at http://***/research/quality/*** for further experimentation.

关键词： Generalized Gaussian scale mixture model Distorted image modeling Distortion-identification No-reference image quality assessment

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Steerable wavelet Frames Based on the Riesz Transform

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IEEE TRANSACTIONS ON image processing 2010年第3期19卷 653-667页

作者： Held, Stefan Storath, Martin Massopust, Peter Forster, Brigitte Tech Univ Munich Zentrum Math Munich Germany Helmholtz Zentrum Munchen Inst Biomath & Biometry Marie Curie Excellence Res Team MAMEBIA Munich Germany

We consider an extension of the 1-D concept of analytical wavelet to n-D which is by construction compatible with rotations. This extension, called a monogenic wavelet, yields a decomposition of the wavelet coefficients into amplitude, phase, and phase direction. The monogenic wavelet is based on the hypercomplex monogenic signal which is defined using Riesz transforms and perfectly isotropic wavelets frames. Employing the new concept of Clifford frames, we can show that the monogenic wavelet generates a wavelet frame. Furthermore, this approach yields wavelet frames that are steerable with respect to direction. applications to descreening and contrast enhancement illustrate the versatility of this approach to image analysis and reconstruction.

关键词： Analytical signal Clifford algebra contrast enhancement descreening Hilbert transform monogenic signal phase phase direction Riesz transform steerable filters wavelet

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Multichannel wavelet correlators for fingerprint identification by the use of associative storage in a photorefractive material

Multichannel wavelet correlators for fingerprint identificat...

引用

Conference on wavelet applications in signal and image processing vi

作者： Yan, YB Huang, GG Feng, WY Jin, GF Wu, MX Tsing Hua Univ State Key Lab Precis Measurement Technol & Instru Beijing 100084 Peoples R China

ISBN: (纸本)0819429139

The application of wavelet transform can improve discrimination capability and signal-to-noise ratio of the correlation outputs with respect to the classical one. The concept of the associative storage in a photorefractive material offers suitable methods to design multichannel correlators for fingerprint identification. An optical system that employs holographic recording in a F-e: LiNbO3 crystal is proposed and experimentally demonstrated for the physical implementation of multichannel wavelet matched correlator. The scale of wavelet filter is optimized according to the robustness to the noise and discriminability of the filter. The photorefractive correlator is used as a ROM in the recognition. When the object beam with an input fingerprint is used for recovering, a set of correlation outputs are obtained in parallel along the directions of the reference beams, and detected by a CCD camera. Experimental results are promising for further use in the practice.

关键词： wavelet transform multichannel correlators photorefractive material fingerprint identification

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wavelet descriptor of planar curves: Theory and applications

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IEEE TRANSACTIONS ON image processing 1996年第1期5卷 56-70页

作者： Chuang, GCH Kuo, CCJ UNIV SO CALIF DEPT ELECT ENGN SYST LOS ANGELES CA 90089 USA UNIV SO CALIF INST SIGNAL & IMAGE PROC LOS ANGELES CA 90089 USA

By using the wavelet transform, we develop a hierarchical planar curve descriptor that decomposes a curve into components of different scales so that the coarsest scale components carry the global approximation information while the finer scale components contain the local detailed information, We show that the wavelet descriptor has many desirable properties such as multiresolution representation, invariance, uniqueness, stability, and spatial localization, A deformable wavelet descriptor is also proposed by interpreting the wavelet coefficients as random variables, The applications of the wavelet descriptor to character recognition and model-based contour extraction from low SNR images are examined, Numerical experiments are performed to illustrate the performance of the wavelet descriptor.

关键词： .wavelet coefficients random variables character Theory and applications contour extraction wavelet Descriptor Curves Theory using the wavelet finer invariance uniqueness comers Fourier descriptor

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A Fast wavelet Packet Transform-based algorithm for numerical solution of image restoration problems in a parallel environment

A Fast Wavelet Packet Transform-based algorithm for numerica...

引用

Conference on wavelet applications in signal and image processing vi

作者： Carracciuolo, L D'Amore, L Murli, A Univ Naples Federico II Naples Italy

ISBN: (纸本)0819429139

We explore the filtering properties of wavelets functions in order to develop accurate and efficient numerical algorithms for image Restoration problems. We propose a parallel implementation for MIMD distributed memory environments. The key insight of our approach is the use of distributed versions of Level 3 Basic Linear Algebra Subprograms as computational building blocks and the use of Basic Linear Algebra Communication Subprograms las communication building blocks for advanced architecture computers. The use of these low-level mathematical software libraries garantees the development of efficient, portable and scalable high-level algorithms and hides many details of the parallelism from the user's point of view. Numerical experiments on a simulated image restoration applications are shown. The parallel software has been tested on a 12 nodes IBM SP2 available at the Center for Research on Parallel Computing and Supercomputers in Naples (Italy).

关键词： image Restoration preconditioning regularization wavelets parallel implementation distributed memory architecture

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A New Fractional Random wavelet Transform for Fingerprint Security

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IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS 2012年第1期42卷 262-275页

作者： Bhatnagar, Gaurav Wu, Q. M. Jonathan Raman, Balasubramanian Univ Windsor Dept Elect & Comp Engn Windsor ON N9B 3P4 Canada Indian Inst Technol Dept Math Roorkee 247667 Uttar Pradesh India

In this correspondence paper, the wavelet transform, which is an important tool in signal and image processing, has been generalized by coalescing wavelet transform and fractional random transform. The new transform, i.e., fractional random wavelet transform (FrRnWT) inherits the excellent mathematical properties of wavelet transform and fractional random transform. Possible applications of the proposed transform are in biometrics, image compression, image transmission, transient signal processing, etc. In this correspondence paper, biometrics is chosen as the primary application;and hence, a new technique is proposed for securing fingerprints during communication and transmission over insecure channel.

关键词： Biometrics chaotic map fractional random wavelet transform fractional wavelet transform security wavelet transform

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Splines - A perfect fit for signal and image processing

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IEEE signal processing MAGAZINE 1999年第6期16卷 22-38页

作者： Unser, M Swiss Fed Inst Technol CH-1015 Lausanne Switzerland

The article provides arguments in favor of an alternative approachthat uses splines, which is equally justifiable on a theoretical basis,and which offers many practical advantages. To reassure the reader whomay be afraid to enter new territory, it is emphasized that one is notlosing anything because the traditional theory is retained as aparticular case (i.e., a spline of infinite degree). The basiccomputational tools are also familiar to a signal processing audience(filters and recursive algorithms), even though their use in the presentcontext is less conventional. The article also brings out the connectionwith the multiresolution theory of the wavelet transform. This articleattempts to fulfil three goals. The first is to provide a tutorial onsplines that is geared to a signal processing audience. The second is togather all their important properties and provide an overview of themathematical and computational tools available; i.e., a road map for thepractitioner with references to the appropriate literature. The thirdgoal is to give a review of the primary applications of splines insignal and image processing

关键词： filtering theory image processing interpolation signal processing signal resolution signal sampling splines (mathematics) wavelet transforms computational tools digital filtering filters mathematical tools multiresolution theory recursive algorithms sign image processing Recursive algorithms Digital filters signal resolution filtering theory signal processing splines (mathematics) wavelet transforms Interpolation Filters signal sampling

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