Browsing DSP Publications by Subject "Wavelet based Signal/Image Processing"
Now showing items 160 of 90

3D Geometry Coding using Mixture Models and the Estimation Quantization Algorithm
(20020901)3D surfaces are used in applications such as animations, 3D object modeling and visualization. The geometries of such surfaces are often approximated using polygonal meshes. This thesis aims to compress 3D geometry meshes ... 
Adaptive Representation of JPEG 2000 Images Using Headerbased Processing
(20020920)To bridge the mismatch between the sizes of images and display devices, we present an efficient and automatic algorithm to create an adaptive image representation called SmartNail. Given a digital image and rectangular ... 
Adaptive Wavelet Transforms for Image Coding
(19971101)We introduce a new adaptive transform for waveletbased image coding. The lifting framework for wavelet construction motivates our analysis and provides new insight into the problem. Since the adaptive transform is nonlinear, ... 
Adaptive Wavelet Transforms for Image Coding
(19971101)We introduce a new adaptive transform for waveletbased image coding. The lifting framework for wavelet construction motivates our analysis and provides new insight into the problem. Since the adaptive transform is nonlinear, ... 
Adaptive Wavelet Transforms via Lifting
(19990115)This paper develops new algorithms for adapted multiscale analysis and signal adaptive wavelet transforms. We construct our adaptive transforms with the <i>lifting scheme</i>, which decomposes the wavelet transform into ... 
Adaptive Wavelet Transforms via Lifting
(19990501)This paper develops new algorithms for adapted multiscale analysis and signal adaptive wavelet transforms. We construct our adaptive transforms with the <i>lifting scheme</i>, which decomposes the wavelet transform into ... 
Adaptive Weighted Highpass Filters Using Multiscale Analysis
(19980701)In this paper, we propose a general framework for studying a class of weighted highpass filters. Our framework, based on a multiscale signal decomposition, allows us to study a wide class of filters and to assess the ... 
Analysis of Multiscale Texture Segmentation using WaveletDomain Hidden Markov Trees
(19991001)This paper describes a technique for estimating the KullbackLeibler (KL) distance between two Hidden Markov Models (HMMs), and for measuring the quality of the estimator. It also provides some results based on applying ... 
Approximation and Compression of Piecewise Smooth Images Using a Wavelet/Wedgelet Geometric Model
(20030901)Inherent to photographlike images are two types of structures: large smooth regions and geometrically smooth edge contours separating those regions. Over the past years, efficient representations and algorithms have been ... 
Bayesian TreeStructured Image Modeling using Waveletdomain Hidden Markov Models
(20010701)Waveletdomain hidden Markov models have proven to be useful tools for statistical signal and image processing. The hidden Markov tree (HMT) model captures the key features of the joint probability density of the wavelet ... 
Bayesian TreeStructured Image Modeling using Waveletdomain Hidden Markov Models
(19990720)Waveletdomain hidden Markov models have proven to be useful tools for statistical signal and image processing. The hidden Markov tree (HMT) model captures the key features of the joint probability density of the wavelet ... 
Bayesian Wavelet Domain Image Modeling using Hidden Markov Trees
(19991001)Waveletdomain hidden Markov models have proven to be useful tools for statiscal signal and image processing. The hidden Markov tree (HMT) model captures the key features o teh join statistics of the wavelet coefficients ... 
Coherent Multiscale Image Processing using Quaternion Wavelets
(20061001)The quaternion wavelet transform (QWT) is a new multiscale analysis tool for geometric image features. The QWT is a near shiftinvariant tight frame representation whose coefficients sport a magnitude and three phases: ... 
Compound Poisson Cascades
(20020501)Multiplicative processes and multifractals proved useful in various applications ranging from hydrodynamic turbulence to computer network traffic, to name but two. Placing multifractal analysis in the more general framework ... 
Detecting Periodic Behavior in Nonstationary Signals
(19981020)This paper presents results on the multiresolution analysis of nonstationary signals with the objective of detecting underlying periodic phenomena. Wavelet packet analysis with coefficient thresholding is the basis for the ... 
Directional ComplexWavelet Processing
(20000820)Poor directional selectivity, a major disadvantage of the separable 2D discrete wavelet transform (DWT), has previously been circumvented either by using highly redundant, nonseparable wavelet transforms or by using ... 
Directional Hypercomplex Wavelets for Multidimensional Signal Analysis and Processing
(20040501)We extend the wavelet transform to handle multidimensional signals that are smooth save for singularities along lowerdimensional manifolds. We first generalize the complex wavelet transform to higher dimensions using a ... 
Directional, ShiftInsensitive, Complex Wavelet Transforms with Controllable Redundancy
(20010820)Although the Discrete Wavelet Transform (DWT) is a powerful tool for signal and image processing, it has three serious disadvantages. First, the DWT is shift sensitive because inputsignal shifts generate unpredictable ... 
Distributed Wavelet Transform for Irregular Sensor Network Grids
(20050701)Waveletbased distributed data processing holds much promise for sensor networks; however, irregular sensor node placement precludes the direct application of standard wavelet techniques. In this paper, we develop a new ... 
Diverging moments and parameter estimation
(20040115)Heavy tailed distributions enjoy increased popularity and become more readily applicable as the arsenal of analytical and numerical tools grows. They play key roles in modeling approaches in networking, finance, hydrology ... 
The DualTree Complex Wavelet Transform
(20051101)The paper discusses the theory behind the dualtree transform, shows how complex wavelets with good properties can be designed, and illustrates a range of applications in signal and image processing. The authors use the ... 
Edge Characteristics in WaveletBased Image Coding
(20010420)Accurate prediction of wavelet coefficients relies on an understanding of the phase effects of edge alignment. This research examines techniques for uncovering edge information based on the available coefficients. These ... 
Efficient Approximation of Continuous Wavelet Transforms
(19910401)An efficient method, based on the chirpz transform, for computing equally spaced time samples of a continuous wavelet transform at arbitrary scale samples is developed. Applications include efficient computation of samples ... 
Efficient Methods for Identification of Volterra Filters
(19960201)A major drawback of the truncated Volterra series or "Volterra filter" for system identification is the large number of parameters required by the standard filter structure. The corresponding estimation problem requires ... 
Enhancement of Decompressed Images at Low Bit Rates
(19940720)Transform coding at low bit rates introduces artifacts associated with the basis functions of the transform. For example, decompressed images based on the DCT (discrete cosine transform) like JPEG<sup>16</sup>  exhibit ... 
EstimationQuantization Geometry Coding Using Normal Meshes
(20030301)We propose a new algorithm for compressing threedimensional triangular mesh data used for representing surfaces. We apply the EstimationQuantization (EQ) algorithm originally designed for still image compression to the ... 
ForWaRD: FourierWavelet Regularized Deconvolution for IllConditioned Systems
(20040201)We propose an efficient, hybrid <i>FourierWavelet Regularized Deconvolution</i> (ForWaRD) algorithm that performs noise regularization via scalar shrinkage in both the Fourier and wavelet domains. The Fourier shrinkage ... 
A Geometric Hidden Markov Tree Wavelet Model
(20030801)In the last few years, it has become apparent that traditional waveletbased image processing algorithms and models have significant shortcomings in their treatment of edge contours. The standard modeling paradigm exploits ... 
Geometric Methods for WaveletBased Image Compression
(20030801)Natural images can be viewed as combinations of smooth regions, textures, and geometry. Waveletbased image coders, such as the spacefrequency quantization (SFQ) algorithm, provide reasonably efficient representations for ... 
Geometric Tools for Image Compression
(20021101)Images typically contain strong geometric features, such as edges, that impose a structure on pixel values and wavelet coefficients. Modeling the joint coherent behavior of wavelet coefficients is difficult, and standard ... 
Geometry Compression of Normal Meshes using RateDistortion Algorithms
(20030601)We propose a new ratedistortion based algorithm for compressing 3D surface geometry represented using triangular normal meshes. We apply the EstimationQuantization (EQ) algorithm to compress normal mesh wavelet coefficients. ... 
Hidden Markov Tree Modeling of Complex Wavelet Transforms
(20000601)Multiresolution signal and image models such as the hidden Markov tree aim to capture the statistical structure of smooth and singular (edgy) regions. Unfortunately, models based on the orthogonal wavelet transform suffer ... 
Hidden Markov Tree Models for Complex Wavelet Transforms
(20020501)Multiresolution models such as the hidden Markov tree (HMT) aim to capture the statistical structure of signals and images by leveraging two key wavelet transform properties: wavelet coefficients representing smooth/singular ... 
Image Compression using an Efficient Edge Cartoon + Texture Model
(20020401)Waveletbased image coders optimally represent smooth regions and isolated point singularities. However, wavelet coders are less adept at representing perceptually important edge singularities, and coding performance ... 
Image Compression using Multiscale Geometric Edge Models
(20020520)Edges are of particular interest for image compression, as they communicate important information, contribute large amounts of highfrequency energy, and can generally be described with few parameters. Many of today's most ... 
Image enhancement by nonlinear wavelet processing
(19941020)In this paper we describe how the theory of wavelet thresholding introduced by Donoho and Johnstone can successfully be applied to two distinct problems in image processing where traditional linear filtering techniques are ... 
Image Restoration Using the EM Algorithm and WaveletBased Complexity Regularization
(20020520)This paper introduces an <i>expectationmaximization</i> (EM) algorithm for image restoration (deconvolution) based on a penalized likelihood formulated in the wavelet domain. Regularization is achieved by promoting a ... 
Improved Wavelet Denoising via Empirical Wiener Filtering
(19970701)Wavelet shrinkage is a signal estimation technique that exploits the remarkable abilities of the wavelet transform for signal compression. Wavelet shrinkage using thresholding is asymptotically optimal in a minimax ... 
LongRange Dependence: Now you see it now you don't!
(20021120)Over the last few years, the network community has started to rely heavily on the use of novel concepts such as selfsimilarity and LongRange Dependence (LRD). Despite their wide use, there is still much confusion regarding ... 
Low Rank Estimation of Higher Order Statistics
(19951201)Low rank estimators for higher order statistics are considered in this paper. Rank reduction methods offer a general principle for trading estimator bias for reduced estimator variance. The biasvariance tradeoff is analyzed ... 
Modelbased Inverse Halftoning with WaveletVaguelette Deconvolution
(20000901)In this paper, we demonstrate based on the linear model of Kite that inverse halftoning is equivalent to the wellstudied problem of deconvolution in the presence of colored noise. We propose the use of the simple and ... 
Multiresolution Intensity Estimation of Piecewise Linear Poisson Processes
(20010420)Given observations of a onedimensional piecewise linear, lengthM Poisson intensity function, our goal is to estimate both the partition points and the parameters of each segment. In order to determine where the breaks ... 
Multiscale Classification using Complex Wavelets and Hidden Markov Tree Models
(20000901)Multiresolution signal and image models such as the hidden Markov tree (HMT) aim to capture the statistical structure of smooth and singular (textured and edgy) regions. Unfortunately, models based on the orthogonalwavelet ... 
A Multiscale Data Representation for Distributed Sensor Networks
(20050301)Though several waveletbased compression solutions for wireless sensor network measurements have been proposed, no such technique has yet appreciated the need to couple a wavelet transform tolerant of irregularly sampled ... 
A Multiscale Data Representation for Distributed Sensor Networks: Proofs of Basis Characteristics and Error Bounds
(20040901)Provides proofs of Parseval tightframe membership and approximation properties for the basis proposed in "A Multiscale Data Representation for Distributed Sensor Networks" by R. Wagner, S. Sarvotham, and R. Baraniuk (ICASSP ... 
Multiscale Density Estimation
(20030820)The nonparametric density estimation method proposed in this paper is computationally fast, capable of detecting density discontinuities and singularities at a very high resolution, spatially adaptive, and offers near ... 
Multiscale Edge Grammars for Complex Wavelet Transforms
(20011001)Wavelet domain algorithms have risen to the forefront of image processing. The power of these algorithms is derived from the fact that the wavelet transform restructures the image in a way that makes statistical modeling ... 
Multiscale Image Segmentation Using Joint Texture and Shape Analysis
(20000701)We develop a general framework to simultaneously exploit texture and shape characterization in multiscale image segmentation. By posing multiscale segmentation as a model selection problem, we invoke the powerful framework ... 
Multiscale Likelihood Analysis and Complexity Penalized Estimation
(20010820)We describe here a framework for a certain class of multiscale likelihood factorization wherein, in analogy to a wavlet decomposition of an LÂ² function, a given likelihood function has an alternative representation as a ... 
Multiscale Likelihood Analysis and Image Reconstruction
(20030820)The nonparametric multiscale polynomial and platelet methods presented here are powerful new tools for signal and image denoising and reconstruction. Unlike traditional waveletbased multiscale methods, these methods are ... 
Multiscale modeling and estimation of Poisson processes with application to photonlimited imaging
(19990420)Many important problems in engineering and science are wellmodeled by Poisson processes. In many applications it is of great interest to accurately estimate the intensities underlying observed Poisson data. In particular, ... 
Multiscale Nature of Network Traffic
(20020501)The complexity and richness of telecommunications traffic is such that one may despair to find any regularity or explanatory principles. Nonetheless, the discovery of scaling behavior in teletraffic has provided hope that ... 
Multiscale SAR Image Segmentation using Waveletdomain Hidden Markov Tree Models
(20000401)We study the segmentation of SAR imagery using waveletdomain Hidden Markov Tree (HMT) models. The HMT model is a treestructured probabilistic graph that captures the statistical properties of the wavelet transforms of ... 
Near Best Tree Approximation
(20020115)Tree approximation is a form of nonlinear wavelet approximation that appears naturally in applications such as image compression and entropy encoding. The distinction between tree approximation and the more familiar ... 
Network Traffic Modeling using a Multifractal Wavelet Model
(19990201)In this paper, we describe a new multiscale model for characterizing positivevalued and longrange dependent data. The model uses the Haar wavelet transform and puts a constraint on the wavelet coefficients to guarantee ... 
A New Framework for Complex Wavelet Transforms
(20030620)Although the Discrete Wavelet Transform (DWT) is a powerful tool for signal and image processing, it has three serious disadvantages: shift sensitivity, poor directionality and lack of phase information. To overcome these ... 
Noise Reduction Using an Undecimated Discrete Wavelet Transform
(19950115)A new nonlinear noise reduction method is presented that uses the discrete wavelet transform. Similar to Donoho and Johnstone, we employ thresholding in the wavelet transform domain but, following a suggestion by Coifman, ... 
Nonlinear Processing of a Shift Invariant DWT for Noise Reduction
(19950420)A novel approach for noise reduction is presented. Similar to Donoho, we employ thresholding in some wavelet transform domain but use a nondecimated and consequently redundant wavelet transform instead of the usual orthogonal ... 
Nonlinear Processing of a Shift Invariant DWT for Noise Reduction
(19950320)A novel approach for noise reduction is presented. Similar to Donoho, we employ thresholding in some wavelet transform domain but use a nondecimated and consequently redundant wavelet transform instead of the usual orthogonal ... 
Nonlinear Wavelet Processing for Enhancement of Images
(19940520)In this note we apply some recent results on nonlinear wavelet analysis to image processing. In particular we illustrate how the (soft) thresholding algorithm due to Donoho and Johnstone can successfully be used to remove ...