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An improved spatially selective filter using undecimated wavelet transform

An improved spatially selective filter using undecimated wav...

引用

IEEE 15th signal processing and Communications applications conference

作者： Zheng, Chuanxing Zhang, Yiming School of Informatics Guizhou College of Finance and Economics China College of Electronic Information and Control Engineering Beijing University of Technology China

ISBN: (纸本)9781424407194

This paper proposes a novel wavelet filtering method by spatial correlation thresholding based on undecimated wavelet transform (UDWT). We multiply two adjacent wavelet scales with some relative translations to line up the edges. A new threshold is presented applying to spatial correlation in our proposed scheme. Finally, we extract edge information from larger scale to smaller one only at the positions which have been extracted as edges. The simulation results indicate that our algorithm can keep edges well while removing noise greatly. It is an effective noise filtration technique especially for the signals which have abundant edge and detail information. Furthermore, it can be easily extended to edge detection, fault diagnosis, image enhancement and other applications.

关键词： wavelet transforms signals filtering image enhancement noise

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image denoising based on scale-space mixture modeling of wavelet coefficients

Image denoising based on scale-space mixture modeling of wav...

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International conference on image processing (ICIP'99)

作者： Liu, Juan Moulin, Pierre Univ of Illinois Urbana United States

In this paper, we propose a novel hierarchical statistical model for image wavelet coefficients. A simple classification scheme is used to construct a model that captures interscale and intrascale dependencies of wavelet coefficients. applications to image denoising are presented. We develop a simple algorithm that outperforms other wavelet denoising schemes that exploit first-order statistics, or inter- or intra- scale dependencies alone.

关键词： image reconstruction

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Systolic Murmurs Diagnosis Improvement by Feature Fusion and Decision Fusion

Systolic Murmurs Diagnosis Improvement by Feature Fusion and...

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IEEE International conference on signal and image processing applications (IEEE ICSIPA)

作者： Akbari, Somayeh Ghassemian, Hassan Akbari, Zahra Tarbiat Modares Univ Fac Elect & Comp Engn Image Proc & Informat Anal Lab Tehran Iran

ISBN: (纸本)9781728133775

Acoustic sound generated by the heart mechanical activity, can provide useful information about the condition of heart valves. The heart sound auscultation is the fundamental tool in the evaluation of the cardiovascular system. The advantage of this method is fast, inexpensive and noninvasive. Due to human auscultatory limitation and non-stationary characteristics of phonocardiogram signals (PCG), diagnosis based on sounds that are heard via a stethoscope is difficult skill, therefor it requires a lot of practice. This study has proposed a biomedical automatic system for classification of PCG signals, which, recorded by a digital stethoscope. In order to extract various characteristics of PCG signals, the power spectrum estimation, wavelet transform (WT) and Mel frequency Cepstrum coefficients (MFCC) have been used in feature extraction step. Features are given to four classifiers: support vector machine (SVM), k-nearest neighbor (k-NN), multilayer perceptron (MLP) and maximum likelihood (ML). The majority voting combination rule is utilized for fusion of different classifiers. The proposed method has been examined on dataset of 90 PCG records containing healthy and three types of cardiac valve diseases (pulmonary stenosis (PS), Atrial Septal Defect (ASD) and Ventricular Septal Defect (VSD)). The experimental results demonstrate that the classifier fusion rule significantly increases the diagnostic accuracy of abnormal PCG. Our proposed method can be used for online classification of PCG in intelligent diagnosis systems.

关键词： PCG signal MFCC algorithm power spectrum estimation wavelet transform feature fusion decision fusion

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Optimizing signal and image processing applications using Intel libraries

Optimizing signal and image processing applications using In...

引用

8th International conference on Quality Control by Artificial Vision

作者： Landre, Jerome Truchetet, Frederic Univ Reims IUT CReSTIC 10 Rue Quebec Troyes France Univ Bourgogne Le Creusot France

ISBN: (纸本)9780819464514

This paper presents optimized signal and image processing libraries from Intel Corporation. Intel Performance Primitives (IPP) is a low-level signal and image processing library developed by Intel Corporation to optimize code on Intel processors. Open Computer Vision library (OpenCV) is a high-level library dedicated to computer vision tasks. This article describes the use of both libraries to build flexible and efficient signal and image processing applications.

关键词： image processing signal processing Machine vision Matrices Computer vision technology Transform theory wavelet transforms Digital signal processing Video image retrieval

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Fusion of Satellite images Usimg Bilateral Filter Based Edge Preserving image Decomposition

Fusion of Satellite Images Usimg Bilateral Filter Based Edge...

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22nd IEEE signal processing and Communications applications conference (SIU)

作者： Kaplan, Nur Huseyin Erer, Isin Istanbul Tech Univ Elekt & Haberlesme Muhendisligi Bolumu Istanbul Turkey

ISBN: (纸本)9781479948741

A new fusion method based on bilateral pyramid for multispectral and panchromatic images is presented. Bilateral pyramid is a multiscale decomposition method which can decompose an input image into a base layer representing the low frequency content and several detail layers representing the high frequency part of the image. The fused image is obtained by three different rules: substitutive, additive and additive luminance proportional methods. The proposed methods are compared with the widely used IHS (intensity-hue-saturation) and ATWT based fusion methods. The resulting images as well as evaluation metrics demonstrate that the proposed algorithm has better performance.

关键词： image fusion pansharpening bilateral filter additive wavelet transform

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Scattered data smoothing by empirical Bayesian shrinkage of second generation wavelet coefficients

Scattered data smoothing by empirical Bayesian shrinkage of ...

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conference on wavelets - applications in signal and image processing IX

作者： Jansen, M Nason, G Silverman, B Rice Univ Dept ECE Houston TX 77251 USA

ISBN: (纸本)0819441929

We propose a novel approach for scattered data smoothing based on second generation wavelets. This wavelet transform automatically adapts to the irregularity of the grid. Our implementation also pays attention to numerical stability, a crucial property in estimation procedures. The wavelet coefficients are shrunk either with simple soft-thresholding or with an empirical Bayesian estimation.

关键词： wavelets wavelet transforms Computer graphics Numerical stability signal processing Statistical analysis Astatine Condition numbers Convolution image processing

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Parallel Implementation of the Discrete wavelet Transform on Graphics processing Units

Parallel Implementation of the Discrete Wavelet Transform on...

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1st International conference on Advanced Technologies for signal and image processing (ATSIP)

作者： Khemiri, Randa Sayadi, Fatma Saidani, Taoufik Chouchene, Marwa Bahri, Haythem Tourki, Rached Univ Monastir Lab Elect & Microelect Fac Sci Monastir Monastir Tunisia

ISBN: (纸本)9781479948888

Discrete wavelet transform (DWT), has diverse applications in signal and image processing fields. In this paper, we have implemented the lifting "Le Gall 5/3" algorithm on a low cost NVIDIA's GPU (Graphics processing unit) with Mat Lab to achieve speedup in computation. The efficiency of our GPU based implementation is measured and compared with CPU based algorithms. Our investigational results with GPU show performance enhancement over a factor of 1.52 compared with CPU for an image of size 3072x3072.

关键词： JPEG2000 Discrete wavelet Transform (DWT) Graphics processing unit (GPU) Parallel computing Central processing unit (CPU) MatLab

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Mixed memory model for image processing and modeling with complex Daubechies wavelets

Mixed memory model for image processing and modeling with co...

引用

conference on wavelet applications in signal and image processing viiI

作者： Clonda, D Lina, JM Goulard, B Univ Montreal Ctr Rech Math Montreal PQ H3C 3J7 Canada

ISBN: (纸本)0819437646

In this paper, we propose a statistical modeling of images based on a decomposition with complex-valued Daubechies wavelets. These wavelets possess interesting properties that can be turn into account in the modeling to obtain a better characterization of the images. This characterization is achieved by statistically modeling the wavelet coefficient distribution via a hidden Markov tree model. The wavelet coefficients in an image are organized into three tree structures and this type of model has already been used successfully in this context by independently modeling each of these trees. We propose a further refinement by considering the joint modeling of the three trees with a so-called mixed memory hidden Markov tree model. The model is based on a memory mixture, a general approach to obtain an approximation of the joint distribution in the presence of factorial Markov models. The utilization of such model is quite general and can be applied to various signal-processing problems. To illustrate the interest of this model as well as the relevance of using complex Daubechies wavelets, we evaluate their performance for a classification and a denoising application.

关键词： complex wavelets Markov model image modeling mixed memory model denoising image processing statistical modeling

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Multiresolution analysis with decimated wavelet transform for image zooming

Multiresolution analysis with decimated wavelet transform fo...

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conference on wavelet applications in signal and image processing viiI

作者： Nicolier, F Truchetet, F IUT Le Creusot Le2i F-71200 Le Creusot France

ISBN: (纸本)0819437646

Blurred images are produced by interpolation process. A wavelet-based magnification method is proposed that both increases the resolution of an image and adds local high-frequency informations, in order to provide digitally zoomed images with sharp edges. wavelet transforms computed by the decimated Mallat's algorithm present pyramidal aspect. This pyramidal analysis combined with a prediction of high-frequency coefficients is used to produce a magnified image. The prediction is based on a zero-crossings representation and on the construction of a multiscale edge-signature database. Performances are evaluated for synthetic and noisy images. A significant improvement regarding some classical methods (spline interpolation) is observed.

关键词： Reconstruction algorithms wavelets wavelet transforms Databases Fast wavelet transforms image processing image quality image resolution Resolution enhancement technologies signal processing

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Arithmetic gain of the Lifting Scheme

Arithmetic gain of the Lifting Scheme

引用

conference on wavelets - applications in signal and image processing IX

作者： Reichel, J VisioWave Corp R&D Ctr CH-1024 Ecublens Switzerland

ISBN: (纸本)0819441929

The Lifting Scheme (LS) is a very efficient implementation of the Discrete wavelet transform (DWT). In this work we compute the arithmetic gain realized when the LS is used instead of conventional filter banks. It is shown that contrary to was was presented in the original work from Sweldens again of four is possible. However the LS should be used with care as it can increase the memory bandwidth. Some implementations are presented together with their impact on the bandwidth.

关键词： Discrete wavelet transforms Optical filters Finite impulse response filters Linear filtering image filtering Electronic filtering image compression Algorithm development Matrices wavelets

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