Analyse Magnéto-Vibroacoustique Des Machines Synchrones Discoides À Commutation De Flux Dédiées Aux Véhiculex Électriques Hybrides Hamza Ennassiri

Total Page:16

File Type:pdf, Size:1020Kb

Analyse Magnéto-Vibroacoustique Des Machines Synchrones Discoides À Commutation De Flux Dédiées Aux Véhiculex Électriques Hybrides Hamza Ennassiri Analyse magnéto-vibroacoustique des machines synchrones discoides à commutation de flux dédiées aux véhiculex électriques hybrides Hamza Ennassiri To cite this version: Hamza Ennassiri. Analyse magnéto-vibroacoustique des machines synchrones discoides à commutation de flux dédiées aux véhiculex électriques hybrides. Autre. Normandie Université, 2018. Français. NNT : 2018NORMLH36. tel-02074386 HAL Id: tel-02074386 https://tel.archives-ouvertes.fr/tel-02074386 Submitted on 20 Mar 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. THESE Pour obtenir le diplôme de doctorat Spécialité Génie électrique Préparée au sein du « Groupe de Recherche en Électrotechnique et Automatique du Havre (EA 3220)» Analyse magnéto-vibroacoustique des machines synchrones discoides à commutation de flux dédiées aux véhicules électriques hybrides. Présentée et soutenue par Hamza ENNASSIRI Thèse soutenue publiquement le (19/12/2018) devant le jury composé de Mr / Vincent LANFRANCHI Professeur des universités à l’Université de Technologie de Compiègne Rapporteur Mr / Jean-Philippe LECOINTE Professeur des universités à l’Université d’Artois - LSEE Rapporteur Mr/ Johan Paulides Docteur, Advanced Electromagnetics BV Examinateur Mr / Guillaume VEREZ Docteur, Chef de projet à Sonceboz Group Examinateur Mr / Mouheb DHIFLI Docteur, design leader chez Valeo Examinateur Mr / Ferhat CHABOUR Docteur, Université Le Havre Normandie Examinateur Mr / Yacine AMARA Professeur des universités à l'Université du Havre Encadrant Mr / Georges BARAKAT Professeur des universités à l'Université du Havre Directeur de thèse Thèse dirigée par Georges BARAKAT, laboratoire GREAH Logo Etablissement Logo Ecole Doctorale Logo laboratoire Remerciement Le travail présenté dans ce mémoire a été réalisé au Laboratoire Groupe de Recherche en Électrotechnique et Automatique du Havre (GREAH) à l’université du Havre. Il a été financé par la région Haute-Normandie. Je tiens à exprimer ma gratitude envers Mr Jean-Philippe LECOINTE, Professeur à l’Université d’Artois et Mr Vincent LANFRANCHI, Professeur à l’Université de Technologie de Compiègne, d’avoir accepté d’être rapporteurs de ce travail. Ma gratitude va également à Mr Johan Paulides, Directeur à Advanced Electromagnetics BV, et Mr Guillaume VEREZ, Chef de projet à Sonceboz Group, d’avoir accepté d’être examinateur de ce travail. Je tiens à remercier très chaleureusement Mr Georges BARAKAT, Professeur à l’université du Havre et directeur du GREAH, qui m’a encadré durant ces trois dernières années. Merci de m’avoir fait confiance ainsi que tes conseils. La participation aux nombreuses conférences m’a apporté le goût de la communication scientifique mais aussi cet esprit critique. Mes remerciements s’adressent également à Mr Yacine AMARA, Professeur à l’université du Havre et chef d’équipe pour son accueil chaleureux et ses encouragements. Que soit remercié Mr Ferhat CHABOUR, Maître de conférences à l’université du Havre, merci pour ta disponibilité et ton savoir. Mes remerciements vont aussi à Mr Mouheb DHIFLI, ingénieur-docteur design leader chez Valeo, pour avoir partagé avec nous sa riche bibliographie et ces travaux de recherche. Je remercie aussi toute l’équipe et personnels du laboratoire GREAH mais aussi mes amis et collègues Mohammed Ali Benhamida, Adel Bellara, Habiba Bali, Mohammed Ammani et Nabih Debbah, pour les diverses collaborations scientifiques, soutiens et partage tout le long de cette thèse. Je tiens à remercier du fond du cœur mes parents Abdellatif et Rachida pour leur soutient inestimable et permanent tout au long de mes études, c’est grâce à eux que j’en suis là aujourd’hui. Ces remerciements vont aussi à mon petit frère Ayoub et ma petite sœur Asmaa. Je terminerais en remerciant du fond du cœur mon amour, ma femme Sonia qui m’a soutenue et supporté durant toute cette thèse. Je te remercie énormément de m’avoir épaulé et aidé dans cette rédaction. Finalement, je dédie cette thèse à tous ceux et celles qui y ont collaboré de près ou de loin. Liste de Publications Articles publiés dans des revues internationales avec comités de lecture Novembre 2017 M. A. Benhamida, H. Ennassiri, M. Dhifli, Y. Amara et G. Barakat Slots & Poles combination influence on the vibro-acoustic behavior of axial type flux switching permanent magnet machines. Journal of Mathematics and Computers in Simulation (MATCOM). (Submitted) Novembre 2017 H. Ennassiri, M. A. Benhamida, M. Dhifli, G. Barakat, Vibro-acoustic response of a discodal switching flux permanent magnet machine due to electromagnetic origin. Journal of Mathematics and Computers in Simulation (MATCOM). (Submitted) Octobre 2017 Benhamida, M. A., Ennassiri, H., Amara, Y., et G. Barakat, Reluctance Network Lumped Mechanical & Thermal Models for the modeling and predesign of concentrated Flux synchronous machine. Open Physics Journal. (Accepted) Janvier 2016 M. Dhifli, H. Ennassiri, F. Chabour, Y. Amara et G. Barakat, Numerical and experimental validation of multi-physics design models for axial flux permanent magnet wind generator. European Journal of Electrical Engineering EJEE, , vol. 18, no. 01-02, pp. 27-60, 2016. Articles présentés dans des conférences nationales et internationales avec comités de lecture Septembre 2017 Reluctance Network & Lumped Mechanical Models for the modeling of concentrated Flux synchronous machine. International Symposium on Electromagnetic Fields in Mechatronics (ISEF), Lodz, Poland. Septembre 2017 Influence of contact coefficients on vibrational behavior of PM machines using a new investigation approach. International Symposium on Electromagnetic Fields in Mechatronics (ISEF), Lodz, Poland. Septembre 2017 Reluctance Network Based Optimization of Large Concentrated Flux Permanent Magnet Wind Generator. International Symposium on Applied Electromagnetics and Mechanics (ISEM), Chamonix Mont Blanc, France. Juillet 2017 Slots and Poles combination influence on the vibro-acoustic behavior of axial type flux switching permanent magnet machines. Electrimacs 2017, Toulouse, France. Juillet 2017 Vibro-acoustic response of a discoïdal switching flux permanent magnet machine due to electromagnetic origin. Electrimacs 2017, Toulouse, France. Octobre 2016 Comparison between Axial type Surface Mounted and Switching Flux Permanent Magnet machines for wind turbine application. Conférence Internationale en Sciences et Technologies Électriques au Maghreb (CISTEM), Marrakech, Maroc. Octobre 2016 Modélisation d'une Machine Synchrone à Double Excitation Série par un circuit de Réluctances Maillé. Conférence Internationale en Sciences et Technologies Électriques au Maghreb (CISTEM), Marrakech, Maroc. Octobre 2016 Interpolation coupling for reluctance network models dedicated to the predesign of Switching Flux Permanent Magnet machines. Conférence Internationale en Sciences et Technologies Électriques au Maghreb (CISTEM), Marrakech, Maroc. Lien Septembre 2016 Impact Of the Airgap Magnetic Field Harmonics On The Performances of A Disc Type Flux Switching Machine For Wind Application. International Conference on Electrical Machines (ICEM), Lausanne, Switzerland. Lien Juin 2016 Couplage électromagnétique vibroacoustique pour l'étude des émissions sonores d'une Machine Synchrone à Rotor Bobiné (MSRB). Symposium de Génie Électrique (SGE), Grenoble, France. Lien Avril 2016 Magneto-vibro-acoustic analysis of a discoidal switching flux permanent magnet machine dedicated to wind turbine application. International Conference on Ecological Vehicles and Renewable Energies (EVER), Monaco. Lien Avril 2016 Steady state hybrid thermal modelling of permanent magnet electrical machines. International Conference on Ecological Vehicles and Renewable Energies (EVER), Monaco. Lien Octobre 2015 Magneto-vibro-acoustic analysis linking FLUX 2D-3D to ANSYS Mechanical. CEDRAT News magazine edition 69, Lyon,France. Lien Septembre 2015 Modeling of axial flux switching permanent magnet machine using magnetic equivalent circuit. International Symposium on Electromagnetic Fields (ISEF), Valencia, Spain. Table des matières Introduction Générale ......................................................................................................................1 PREAMBULE...................................................................................................................................7 P.I. Notions de mécanique vibratoire ..........................................................................................9 P.I.1. Définition ....................................................................................................................9 P.I.2. Instabilité vibratoire .....................................................................................................9 P.I.3. Atténuation des vibrations ............................................................................................9 P.I.4. Résonance vibratoire .................................................................................................. 10 P.I.5. Analyse modale ........................................................................................................
Recommended publications
  • Oriented Half Gaussian Kernels and Anisotropic Diffusion Baptiste Magnier, Philippe Montesinos
    Oriented half Gaussian kernels and anisotropic diffusion Baptiste Magnier, Philippe Montesinos To cite this version: Baptiste Magnier, Philippe Montesinos. Oriented half Gaussian kernels and anisotropic diffusion. 9th International Conference on Computer Vision Theory and Applications, VISAPP 2014; Lisbon; Portugal; 5 January 2014 through 8 January 2014; Code 107286, Jan 2014, Lisbonne, Portugal. pp.2945-2956. hal-01940388 HAL Id: hal-01940388 https://hal.archives-ouvertes.fr/hal-01940388 Submitted on 30 Nov 2018 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Oriented Half Gaussian Kernels and Anisotropic Diffusion Baptiste Magnier and Philippe Montesinos Ecole des Mines dALES, LGI2P, Parc Scientifique G.Besse, 30035 Nˆımes Cedex fbaptiste.magnier, [email protected] Keywords: Half anisotropic Gaussian kernel, diffusion PDEs. Abstract: Nonlinear PDEs (partial differential equations) offer a convenient formal framework for image regularization and are at the origin of several efficient algorithms. In this paper, we present a new approach which is based (i) on a set of half Gaussian kernel filters, and (ii) a nonlinear anisotropic PDE diffusion. On one hand, half Gaussian kernels provide oriented filters whose flexibility enables to detect edges with great accuracy.
    [Show full text]
  • Two Enhanced Fourth Order Diffusion Models for Image Denoising
    Journal of Mathematical Imaging and Vision manuscript No. (will be inserted by the editor) Two Enhanced Fourth Order Diffusion Models for Image Denoising Patrick Guidotti · Kate Longo Received: date / Accepted: date Abstract This paper presents two new higher order In this paper, only grey scale images are considered, so diffusion models for removing noise from images. The u is a scalar valued function taking on quantized integer models employ fractional derivatives and are modifi- values between 0 and 255. u is an observed image, con- cations of an existing fourth order partial differential sisting of a “true” image v polluted with noise n. To de- equation (PDE) model which was developed by You and noise an image is to recover v from the observed image Kaveh as a generalization of the well-known second or- u, a theoretically impossible task. Indeed fine details of der Perona-Malik equation. The modifications serve to an image can be indistinguishable from noise and all cure the ill-posedness of the You-Kaveh model without known denoising methods can cause various degrees of sacrificing performance. Also proposed in this paper is blurring, staircasing, and other artifacts. a simple smoothing technique which can be used in nu- Noise reduction, in particular PDE-based noise re- merical experiments to improve denoising and reduce duction, has been a subject of much research since a processing time. Numerical experiments are shown for seminal paper by Perona and Malik in 1990 [29] which comparison. introduced the then novel paradigm of using nonlin- ear diffusions for the task of denoising images.
    [Show full text]
  • The Structural Acoustic Properties of Stiffened Shells
    Downloaded from orbit.dtu.dk on: Sep 27, 2021 The structural acoustic properties of stiffened shells Luan, Yu Published in: Acoustical Society of America. Journal Link to article, DOI: 10.1121/1.2932806 Publication date: 2008 Document Version Publisher's PDF, also known as Version of record Link back to DTU Orbit Citation (APA): Luan, Y. (2008). The structural acoustic properties of stiffened shells. Acoustical Society of America. Journal, 123(5), 3063-3063. https://doi.org/10.1121/1.2932806 General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. Users may download and print one copy of any publication from the public portal for the purpose of private study or research. You may not further distribute the material or use it for any profit-making activity or commercial gain You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. MONDAY MORNING, 30 JUNE 2008 AMPHI GRAND, 8:40 TO 11:50 A.M. Session 1aID Opening Ceremony 1a MON. AM The Opening Ceremony will include a special welcome from the Vice-President of Ile de France Regional Council, addresses by National sponsors, and addresses by the Presidents of the Acoustical Society of America, the European Acoustics Association, and the French Acoustical Society.
    [Show full text]
  • Anisotropic Diffusion in Image Processing
    Anisotropic diffusion in image processing Tomi Sariola Advisor: Petri Ola September 16, 2019 Abstract Sometimes digital images may suffer from considerable noisiness. Of course, we would like to obtain the original noiseless image. However, this may not be even possible. In this thesis we utilize diffusion equations, particularly anisotropic diffusion, to reduce the noise level of the image. Applying these kinds of methods is a trade-off between retaining information and the noise level. Diffusion equations may reduce the noise level, but they also may blur the edges and thus information is lost. We discuss the mathematics and theoretical results behind the diffusion equations. We start with continuous equations and build towards discrete equations as digital images are fully discrete. The main focus is on iterative method, that is, we diffuse the image step by step. As it occurs, we need certain assumptions for these equations to produce good results, one of which is a timestep restriction and the other is a correct choice of a diffusivity function. We construct an anisotropic diffusion algorithm to denoise images and compare it to other diffusion equations. We discuss the edge-enhancing property, the noise removal properties and the convergence of the anisotropic diffusion. Results on test images show that the anisotropic diffusion is capable of reducing the noise level of the image while retaining the edges of image and as mentioned, anisotropic diffusion may even sharpen the edges of the image. Contents 1 Diffusion filtering 3 1.1 Physical background on diffusion . 3 1.2 Diffusion filtering with heat equation . 4 1.3 Non-linear models .
    [Show full text]
  • 22Nd International Congress on Acoustics ICA 2016
    Page intentionaly left blank 22nd International Congress on Acoustics ICA 2016 PROCEEDINGS Editors: Federico Miyara Ernesto Accolti Vivian Pasch Nilda Vechiatti X Congreso Iberoamericano de Acústica XIV Congreso Argentino de Acústica XXVI Encontro da Sociedade Brasileira de Acústica 22nd International Congress on Acoustics ICA 2016 : Proceedings / Federico Miyara ... [et al.] ; compilado por Federico Miyara ; Ernesto Accolti. - 1a ed . - Gonnet : Asociación de Acústicos Argentinos, 2016. Libro digital, PDF Archivo Digital: descarga y online ISBN 978-987-24713-6-1 1. Acústica. 2. Acústica Arquitectónica. 3. Electroacústica. I. Miyara, Federico II. Miyara, Federico, comp. III. Accolti, Ernesto, comp. CDD 690.22 ISBN 978-987-24713-6-1 © Asociación de Acústicos Argentinos Hecho el depósito que marca la ley 11.723 Disclaimer: The material, information, results, opinions, and/or views in this publication, as well as the claim for authorship and originality, are the sole responsibility of the respective author(s) of each paper, not the International Commission for Acoustics, the Federación Iberoamaricana de Acústica, the Asociación de Acústicos Argentinos or any of their employees, members, authorities, or editors. Except for the cases in which it is expressly stated, the papers have not been subject to peer review. The editors have attempted to accomplish a uniform presentation for all papers and the authors have been given the opportunity to correct detected formatting non-compliances Hecho en Argentina Made in Argentina Asociación de Acústicos Argentinos, AdAA Camino Centenario y 5006, Gonnet, Buenos Aires, Argentina http://www.adaa.org.ar Proceedings of the 22th International Congress on Acoustics ICA 2016 5-9 September 2016 Catholic University of Argentina, Buenos Aires, Argentina ICA 2016 has been organised by the Ibero-american Federation of Acoustics (FIA) and the Argentinian Acousticians Association (AdAA) on behalf of the International Commission for Acoustics.
    [Show full text]
  • Based Non-Linear Anisotropic Diffusion Techniques for Image Denoising
    Preprint UCRL-JC-151493 A comparison of PDE- based non-linear anisotropic diffusion techniques for image denoising S. K. Weeratunga and C. Kamath This article was submitted to Image Processing: Algorithms and Systems II, SPIE Electronic Imaging, Santa Clara, January 2003. U.S. Department of Energy Lawrence Livermore National December 23, 2002 Laboratory Approved for public release; further dissemination unlimited DISCLAIMER This document was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the University of California nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or the University of California. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or the University of California, and shall not be used for advertising or product endorsement purposes. This is a preprint of a paper intended for publication in a journal or proceedings. Since changes may be made before publication, this preprint is made available with the understanding that it will not be cited or reproduced without the permission of the author. This report has been reproduced directly from the best available copy.
    [Show full text]
  • Difference Curvature Driven Anisotropic Diffusion for Image Denoising Using Laplacian Kernel
    Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013) Difference Curvature Driven Anisotropic Diffusion for Image Denoising Using Laplacian Kernel Yiyan WANG1,2 Zhuoer WANG3 1. Department of Physics and Engineering Technology Sichuan University of Arts and Science Dazhou, China 2. Laboratory of Image Science and Technology School of Computer Science and Engineering Southeast University Nanjing, China E-mail: [email protected] 3. Library of Sichuan University of Arts and Science Dazhou, China E-mail: [email protected] Abstract—Image noise removal forms a significant preliminary signal as an initial value. However, this model is referred as step in many machine vision tasks, such as object detection and isotropic diffusion. The disadvantage of isotropic diffusion pattern recognition. The original anisotropic diffusion is that it is symmetric and orientation insensitive, leading denoising methods based on partial differential equation often into blurred edges. Perona and Malik(PM)[4] developed an suffer the staircase effect and the loss of edge details when the anisotropic diffusion process as a nonlinear image noise image contains a high level of noise. Because its controlling removal method, which analogized heat diffusion to function is based on gradient, which is sensitive to noise. To adaptively remove the noise of the images. The main idea of alleviate this drawback, a novel anisotropic diffusion algorithm anisotropic diffusion is that it encourages intra-region is proposed. Firstly, we present a new controlling function smoothing and discourages inter-region at the edges[5]. The based on Laplacian kernel, then making use of the local analysis of an image, we propose a difference curvature driven decision on local smoothing is based on a diffusion to describe the intensity variations in images.
    [Show full text]
  • An Auditory Cortex Model for Sound Processing
    An auditory cortex model for sound processing Rand Asswad1, Ugo Boscain2[0000−0001−5450−275X], Dario Prandi1[0000−0002−8156−5526], Ludovic Sacchelli3[0000−0003−3838−9448], and Giuseppina Turco4[0000−0002−5963−1857] 1 Universit´eParis-Saclay, CNRS, CentraleSup`elec,Laboratoire des signaux et syst`emes,91190, Gif-sur-Yvette, France frand.asswad, [email protected] 2 CNRS, LJLL, Sorbonne Universit´e,Universit´ede Paris, Inria, Paris, France [email protected] 3 Universit´eLyon, Universit´eClaude Bernard Lyon 1, CNRS, LAGEPP UMR 5007, 43 bd du 11 novembre 1918, F-69100, Villeurbanne, France [email protected] 4 CNRS, Laboratoire de Linguistique Formelle, UMR 7110, Universit´ede Paris, Paris, France [email protected] Abstract. The reconstruction mechanisms built by the human auditory system during sound reconstruction are still a matter of debate. The pur- pose of this study is to refine the auditory cortex model introduced in [9], and inspired by the geometrical modelling of vision. The algorithm transforms the degraded sound in an 'image' in the time-frequency do- main via a short-time Fourier transform. Such an image is then lifted in the Heisenberg group and it is reconstructed via a Wilson-Cowan differo-integral equation. Numerical experiments on a library of speech recordings are provided, showing the good reconstruction properties of the algorithm. Keywords: Auditory cortex · Heisenberg group · Wilson-Cowan equa- tion · Kolmogorov operator. 1 Introduction Human capacity for speech recognition with reduced intelligibility has mostly been studied from a phenomenological and descriptive point of view (see [18] for a review on noise in speech, as well as a wide range of situations in [2, 17]).
    [Show full text]
  • Anisotropic Total Variation Filtering
    Anisotropic Total Variation Filtering Markus Grasmair Frank Lenzen Computational Science Center Heidelberg Collaboratory University of Vienna for Image Processing Vienna, Austria University of Heidelberg Heidelberg, Germany [email protected] [email protected] April 29, 2010 Abstract Total variation regularization and anisotropic filtering have been es- tablished as standard methods for image denoising because of their ability to detect and keep prominent edges in the data. Both methods, however, introduce artifacts: In the case of anisotropic filtering, the preservation of edges comes at the cost of the creation of additional structures out of noise; total variation regularization, on the other hand, suffers from the stair-casing effect, which leads to gradual contrast changes in homo- geneous objects, especially near curved edges and corners. In order to circumvent these drawbacks, we propose to combine the two regulariza- tion techniques. To that end we replace the isotropic TV semi-norm by an anisotropic term that mirrors the directional structure of either the noisy original data or the smoothed image. We provide a detailed existence the- ory for our regularization method by using the concept of relaxation. The numerical examples concluding the paper show that the proposed intro- duction of an anisotropy to TV regularization indeed leads to improved denoising: the stair-casing effect is reduced while at the same time the creation of artifacts is suppressed. MSC: 68U10, 49J45. 1 Introduction Because of unavoidable inaccuracies inherent in every data acquisition process, it is not possible to recover a precise images from incoming signals. Instead, the recorded data are defective in various manners.
    [Show full text]
  • Sparse Norm Filtering
    Sparse Norm Filtering Chengxi Ye†, Dacheng Tao‡, Mingli Song§, David W. Jacobs†, Min Wu† †Department of Computer Science, University of Maryland ‡Centre for Quantum Computation and Intelligent Systems, University of Technology Sydney §College of Computer Science, Zhejiang University (a) (b) (c) Figure 1: Examples of filtering results using different norms. (a) Left: original image Middle: smoothed image via minimizing l0 energy. Right: sharpened image. (b) Up: image with pepper and salt noise. Down: smoothed result by minimizing the l1 norm. (c) Left: drag-and-drop editing. Right: seamlessly editing using l2 norm filtering. Abstract studied for decades and have been proven to be critical for a wide variety of applications including blurring, sharpening, Optimization-based filtering smoothes an image by minimiz- stylization and edge detection. ing a fidelity function and simultaneously preserves edges by exploiting a sparse norm penalty over gradients. It has ob- In general, existing edge-preserving filtering techniques can tained promising performance in practical problems, such as be classified into the following two groups: weighted average detail manipulation, HDR compression and deblurring, and filtering and optimization-based filtering. thus has received increasing attentions in fields of graphics, computer vision and image processing. This paper derives Well-known techniques of weighted average filtering includes a new type of image filter called sparse norm filter (SNF) anisotropic diffusion [Perona and Malik 1990; Black and from optimization-based filtering. SNF has a very simple Sapiro 1998] and bilateral filtering [Tomasi and Manduchi form, introduces a general class of filtering techniques, and 1998]. Anisotropic diffusion uses the gradients of each pixel explains several classic filters as special implementations of to guide a diffusion process and avoids blurring across edges.
    [Show full text]
  • Anisotropic Diffusion Filtering Followed by Total Variation Denoising
    International Journal of Applied Information Systems (IJAIS) – ISSN : 2249-0868 Foundation of Computer Science FCS, New York, USA Volume 5 – No. 10, August 2013 – www.ijais.org A New Despeckling Method in Ultrasonography: Anisotropic Diffusion Filtering Followed by Total Variation Denoising Kai Wang Yingjie Liu Liwen Zhang School of Information Science School of Information Science Department of Ultrasonography, and Engineering, Lanzhou and Engineering, Lanzhou People’s Hospital of Gansu University University Province Lanzhou 730000, China Lanzhou 730000, China Lanzhou 730000, China ABSTRACT 2. MODEL OF SPECKLE This paper proposes a novel hybrid method to reduce speckle An effective despeckling category requires a reasonable and noise in ultrasonography. This method applies the total accurate statistical model of speckle. Speckle is a form of variation denoising algorithm to the output image of a locally correlated multiplicative noise. Throughout this paper, recently reported anisotropic diffusion filter. Performance of the following equation is employed as the generalized model the proposed method is illustrated using simulated and clinical for speckle: images. Experimental results indicate the proposed method outperforms the existing despeckling schemes in terms of both I Jn (1) speckle reduction and edge preservation. where I represents the observed image, n denotes the noise Keywords introduced by the acquisition of ultrasound images, and J is Speckle, anisotropic diffusion, total variation denoising. the noise free image that needs restoring [1]. 1. INTRODUCTION 3. METHODS Ultrasonography (also called ultrasound imaging) is a widely 3.1 Anisotropic Diffusion used diagnostic instrument, which provides clinician with Anisotropic diffusion was introduced by Perona and Malik real-time images for diagnosis and therapy.
    [Show full text]
  • Medical Image Denoising Using Convolutional Denoising Autoencoders
    Medical image denoising using convolutional denoising autoencoders Lovedeep Gondara Department of Computer Science Simon Fraser University [email protected] Abstract—Image denoising is an important pre-processing step image denoising performance for their ability to exploit strong in medical image analysis. Different algorithms have been pro- spatial correlations. posed in past three decades with varying denoising performances. More recently, having outperformed all conventional methods, In this paper we present empirical evidence that stacked deep learning based models have shown a great promise. These denoising autoencoders built using convolutional layers work methods are however limited for requirement of large training well for small sample sizes, typical of medical image sample size and high computational costs. In this paper we show databases. Which is in contrary to the belief that for optimal that using small sample size, denoising autoencoders constructed performance, very large training datasets are needed for models using convolutional layers can be used for efficient denoising based on deep architectures. We also show that these methods of medical images. Heterogeneous images can be combined to can recover signal even when noise levels are very high, at the boost sample size for increased denoising performance. Simplest point where most other denoising methods would fail. of networks can reconstruct images with corruption levels so high that noise and signal are not differentiable to human eye. Rest of this paper is organized as following, next section Keywords—Image denoising, denoising autoencoder, convolu- discusses related work in image denoising using deep architec- tional autoencoder tures. Section III introduces autoencoders and their variants. Section IV explains our experimental set-up and details our empirical evaluation and section V presents our conclusions I.
    [Show full text]