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检索条件"任意字段=Conference on Wavelets - Applications in Signal and Image Processing IX"

共 642 条记录，以下是161-170 订阅

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Bayesian spherical wavelet shrinkage: applications to shape analysis

Bayesian spherical wavelet shrinkage: Applications to shape ...

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conference on Wavelet applications in Industrial processing V

作者： Le Faucheur, Xavier Vidakovic, Brani Tannenbaum, Allen Georgia Inst Technol Sch Elect & Comp Engn Atlanta GA 30332 USA Georgia Inst Technol Dept Biomed Engn Atlanta GA 30332 USA

ISBN: (纸本)9780819469236

Multiscale analysis has become indispensable in image processing and computer vision. Our work is motivated by the need to efficiently represent 3D shapes that exhibit a spherical topology. This note presents a wavelet based model for shape denoising and data compression. The 3D shape signal is first encoded using biorthogonal spherical wavelet functions defined on a 3D triangulated mesh. We propose a Bayesian shrinkage model for this type of second generation wavelets in order to eliminate wavelet coefficients that likely correspond to noise. This way, we are able to reduce dimension without losing significant information by estimating a noiseless version of our shape.

关键词： shape analysis spherical wavelets wavelet shrinkage Bayesian model

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A Bayesian approach of hyperanalytic wavelet transform based denoising

A Bayesian approach of hyperanalytic wavelet transform based...

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IEEE International Symposium on Intelligent signal processing

作者： Adam, Ioana Nafornita, Corina Boucher, Jean-Marc Isar, Alexandru Polytech Univ Elect & Telecommun Fac Dept Commun Timisoara Romania CNRS ENST Bretagne GET Dept SC Brest France

ISBN: (纸本)9781424408290

The property of shift-invariance associated with a good directional selectivity is important for the application of a wavelet transform, (WT), in many fields of image processing. Generally, complex wavelet transforms, like for example the Double Tree Complex Wavelet Transform, (DTCWT), have these good properties. In this paper we propose the use of a new implementation of such a WT, recently introduced, namely the hyperanalytic, wavelet transform, (HWT), in denoising applications. The proposed denoising method is very simple, implying three steps: the computation of the forward WT, the filtering in the wavelets domain and the computation of the Inverse WT, (IWT). The goal of this paper is the association of a new implementation of the HWT, recently proposed, with a maximum a posteriori (MAP) filter. Some simulation examples and comparisons prove the performances of the proposed denoising method.

关键词： directional selectivity hyperanalytic wavelet transform image denoising maximum a posteriori filter

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Content adaptive wavelet based method for joint denoising of depth and luminance images

Content adaptive wavelet based method for joint denoising of...

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conference on Wavelet applications in Industrial processing V

作者： Jovanov, Ljubomir Petrovic, Nemanja Pizurica, Aleksandra Philips, Wilfried Univ Ghent Telecommun & Informat Proc Dept B-9000 Ghent Belgium

ISBN: (纸本)9780819469236

In this paper we present a new method for joint denoising of depth and luminance images produced by time-of-flight camera. Here we assume that the sequence does not contain outlier points which can be present in the depth images. Our method first performs estimation of noise and signal covariance matrices and then performs vector denoising. Luminance image is segmented into similar contexts usina k-means algorithm, which are used for calculation of covariance matrices. Denoising results are compared with the ground truth images obtained by averaging of the multiple frames of the still scene.

关键词： depth images wavelets noise estimation denoising

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Morphological diversity and sparsity: new insights into multivariate data analysis

Morphological diversity and sparsity: new insights into mult...

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conference on wavelets XII

作者： Bobin, J. Fadili, J. Moudden, Y. Starck, J. -L. CEA Saclay Serv Astrophys SEDI SAP DAPNIA F-91191 Gif Sur Yvette France ENSICAEN GREYC CNRS UMR 6072 Image Proc Grp F-14050 Caen France

ISBN: (纸本)9780819468499

Over the last few years, the development of multi-channel sensors motivated interest in methods for the coherent processing of multivariate data. From blind source separation (BSS) to multi/hyper-spectral data restoration, an extensive work has already been dedicated to multivariate data processing. Previous work(1) has emphasized on the fundamental role played by sparsity and morphological diversity to enhance multichannel signal processing. Morphological diversity(2,3) has been first introduced in the mono-channel case to deal with contour/texture extraction. The morphological diversity concept states that the data are the linear combination of several so-called morphological components which are sparse in different incoherent representations. In that setting, piecewise smooth features (contours) and oscillating components (textures) are separated based on their morphological differences assuming that contours (respectively textures) are sparse in the Curvelet representation (respectively Local Discrete Cosine representation). In the present paper, we define a multichannel-based framework for sparse multivariate data representation. We introduce an extension of morphological diversity to the multichannel case which boils down to assuming that each multichannel morphological component is diversely sparse spectrally and/or spatially. We propose the Generalized Morphological Component Analysis algorithm (GMCA) which aims at recovering the so-called multichannel morphological components. Hereafter, we apply the GMCA framework to two distinct multivariate inverse problems : blind source separation (BSS) and multichannel data restoration. In the two aforementioned applications, we show that GMCA provides new and essential insights into the use of morphological diversity and sparsity for multivariate data processing. Further details and numerical results in multivariate image and signal processing will be given illustrating the good performance of GMCA in those distinct

关键词： morphological diversity sparsity overcomplete representation curvelets wavelets multichannel data blind source separation denoising inpainting

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Clouds removal from remotely sensed images by using a bandelet-based reconstruction technique

Clouds removal from remotely sensed images by using a bandel...

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conference on Wavelet applications in Industrial processing V

作者： Maalouf, Aldo Carre, Philippe Augereau, Bertrand Fernandez-Maloigne, Christine Univ Politiers Signal Image Communicat Lab F-86962 Futuroscope France

ISBN: (纸本)9780819469236

The recurrent presence of clouds and clouds shadows in aerial or remotely sensed images is an awkward problem that severely limits the regular exploitations capability of these images. Removing cloud-contaminated portions of the image and then filling in the missing data represent an important photo editing cumbersome task. The intent of this work is to propose a technique for the reconstruction of areas obscured by clouds in a remotely sensed image. To this end, a new efficient reconstruction technique for missing data synthesis is presented. This technique is based on the Bandelet transform and the multiscale geometrical grouping. It consists of two steps. In the first step, the curves of geometric flow of different zones of the image are determined by using the Bandelet transform with multiscale grouping. This step allows a better representation of the multiscale geometry of the image's structures. Having well represented this geometry, the information inside the cloud-contaminated zone is synthesized by propagating the geometrical flow curves inside that zone. This step is accomplished by minimizing, a functional whose role is to reconstruct the missing or cloud contaminated zone independently of the size and topology of the reconstruction or inpainting domain. Thus, the flow lines are well tied inside the cloud-contaminated zone. The proposed technique is illustrated with some examples on processing multispectral aerial images. The obtained results are compared with those obtained by other clouds removal techniques.

关键词： Clouds wavelets image classification image processing Reconstruction algorithms Wavelet transforms image segmentation Lithium Remote sensing Multispectral imaging

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Video coding with fully separable wavelet and wavelet packet transforms

Video coding with fully separable wavelet and wavelet packet...

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conference on Visual Communications and image processing 2007

作者： Trocan, Maria Pesquet-Popescu, Beatrice GET ENST Signal & Image Proc Dept 37-39 Rue F-75014 Paris France

ISBN: (纸本)9780819466211

Three-dimensional (t+2D) wavelet coding schemes have been demonstrated to be efficient techniques for video compression applications. However, the separable wavelet transform used for removing the spatial redundancy allows a limited representation of the 2D texture because of spatial isotropy of the wavelet basis functions. In this case, anisotropic transforms, such as fully separable wavelet transforms (FSWT), can represent a solution for spatial decorrelation. FSWT inherits the separability, the computational simplicity and the filter bank characteristics of the standard 2D wavelet transform, but it improves the representation of directional textures, as the ones which can be found in temporal detail frames of t + 2D decompositions. The extension of both classical wavelet and wavelet-packet transforms to fully separable decompositions preserve at the same time the low-complexity and best-bases selection algorithms of these ones. We apply these transforms in t + 2D video coding schemes and compare them with classical decompositions.

关键词： wavelets Transform theory Wavelet transforms Video coding Video 3D video compression image processing Video compression 3D image processing Wavelet packet decomposition

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wavelets: A versatile tool for the high frequency surface wave radar

Wavelets: A versatile tool for the high frequency surface wa...

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IEEE 2007 Radar conference

作者： Jangal, Florent Saillant, Stéphane Hélier, Marc Office National d'Etudes et de Recherches Aérospatiales French Aerospace Lab. Chemin de la Hunière 91120 Palaiseau France Université Pierre et Marie Curie - Paris 6 3 rue Galilée 94200 Ivry-sur-Seine France

ISBN: (纸本)1424402840

Widely used in image processing, wavelets seem to be a promising versatile tool for the High Frequency Surface Wave Radar (HFSWR). HFSWR is based on the ability of HF waves (3 MHz to 30 MHz) to propagate along the earth curvature. HFSWR can detect targets up to few hundred kilometers beyond the horizon. The two main applications of the HFSWR are the maritime surveillance of the Exclusive Economic Zone (EEZ) and the remote sensing of the sea. Beside the classical noise which affects all radar signals, the detection capabilities of HFSWR suffer from two limitations: the sea clutter and the ionospheric clutter which are target masks. However sea clutter can be used to perform remote sensing of the sea. In this paper we are studying how wavelets may contribute to the improvement of radar signal processing. We consider general de-noising feature for radar signals, we carry out a wavelet-based improvement of remote sensing of oceanographie parameters and we show the first results of a wavelet-based processing for ionospheric clutter mitigation. © 2007 IEEE.

关键词： Radar systems

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Multi-level signature based biometric authentication using watermarking

Multi-level signature based biometric authentication using w...

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conference on Mobile Multimedia/image processing for Military and Security applications

作者： Maiorana, Emanuele Campisi, Patrizio Neri, Alessandro Univ Roma Tre Dip Elettr Applicata Via Vasca Navale 84 I-00146 Rome Italy

ISBN: (纸本)9780819467010

In the last decade a lot of efforts have been devoted to the development of biometrics-based authentication systems. In this paper we propose a signature-based biometric authentication system, where watermarking techniques are used to embed some dynamic signature features in a static representation of the signature itself, stored either in a centralized database or in a smartcard. The user authentication can be performed either by using some static features extracted from the acquired signature or by using both the aforementioned static features together with the dynamic features embedded in the enrollment stage. A multi-level authentication system, which is capable to provide various degree of security, is thus obtained. The proposed watermarking techniques are tailored to images with sharp edges, like a signature picture, in order to obtain a robust embedding method while keeping intact the original structure of the host signal. Experimental results show the two different levels of security which can be reached when either static features or both static and dynamic features are employed in the authentication process.

关键词： Digital watermarking Biometrics Radon Radon transform Feature extraction image segmentation wavelets CRTs Information security Databases

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2007 IWSSIP and EC-SIPMCS - Proceedings of 2007 14th International Workshop on Systems, signals and image processing, IWSSIP and 6th EURASIP conference Focused on Speech and image processing, Multimedia Communications and Services, EC-SIPMCS

2007 IWSSIP and EC-SIPMCS - Proceedings of 2007 14th Interna...

引用

14th International conference on Systems signals and image processing, IWSSIP 2007 and 6th EURASIP conference Focused on Speech and image processing, Multimedia Communications and Services, EC-SIPMCS 2007

ISBN: (纸本)9789612480295

The proceedings contain 155 papers. The topics discussed include: two fundamental challenges in perceptual coding and image restoration;robust recognition-by-parts using transduction and boosting with applications to biometrics;overview of multi-view video coding;data protection techniques, cryptographic protocols and PKI systems in modern computer networks;analysis of fused ophthalmologic image data;threshold estimation for wavelet domain filtering of signal-dependent noise;partial realization of a generalized transfer function;analysis of electrocardiograms using the convolution kernel compensation approach;using fractal dimension as texture discriminator for content base image retrieval;image interpolation method based on wavelets;face feature detection for 3D model of talking head with speech synthesis;chromatic enhancement technique for JPEG image;and a formal approach to hypervideo design.

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Steerable Filters Generated with the Hypercomplex Dual-Tree Wavelet Transform

Steerable Filters Generated with the Hypercomplex Dual-Tree ...

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IEEE International conference on signal processing and Communications, ICSPC

作者： J. Wedekind B. Amavasai K. Dutton MMVL Materials and Engineering Research Institute Sheffield Hallam University UK

The use of wavelets in the image processing domain is still in its infancy, and largely associated with image compression. With the advent of the dual-tree hypercomplex wavelet transform (D-HWT) and its improved shift invariance and directional selectivity, applications in other areas of image processing are more conceivable. This paper discusses the problems and solutions in developing the DHWT and its inverse. It also offers a practical implementation of the algorithms involved. The aim of this work is to apply the DHWT in machine vision. Tentative work on a possible new way of feature extraction is presented. The paper shows that 2-D hypercomplex basis wavelets can be used to generate steerable filters which allow rotation as well as translation.

关键词： Wavelet transforms image processing Discrete wavelet transforms Wavelet analysis Optical filters Biomedical signal processing Feature extraction Filter bank Equations Wavelet domain

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