179 research outputs found

    On the Relationship between Integer Lifting and Rounding Transform

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    In this paper we analyze the relationship between integer Lifting scheme and Rounding transform as means to compute the wavelet transform in signal processing area. We bring some new results which better describe relationship, reversibility and equivalence of integer lifting scheme and rounding transform concept

    Discrete Wavelet Transforms

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    The discrete wavelet transform (DWT) algorithms have a firm position in processing of signals in several areas of research and industry. As DWT provides both octave-scale frequency and spatial timing of the analyzed signal, it is constantly used to solve and treat more and more advanced problems. The present book: Discrete Wavelet Transforms: Algorithms and Applications reviews the recent progress in discrete wavelet transform algorithms and applications. The book covers a wide range of methods (e.g. lifting, shift invariance, multi-scale analysis) for constructing DWTs. The book chapters are organized into four major parts. Part I describes the progress in hardware implementations of the DWT algorithms. Applications include multitone modulation for ADSL and equalization techniques, a scalable architecture for FPGA-implementation, lifting based algorithm for VLSI implementation, comparison between DWT and FFT based OFDM and modified SPIHT codec. Part II addresses image processing algorithms such as multiresolution approach for edge detection, low bit rate image compression, low complexity implementation of CQF wavelets and compression of multi-component images. Part III focuses watermaking DWT algorithms. Finally, Part IV describes shift invariant DWTs, DC lossless property, DWT based analysis and estimation of colored noise and an application of the wavelet Galerkin method. The chapters of the present book consist of both tutorial and highly advanced material. Therefore, the book is intended to be a reference text for graduate students and researchers to obtain state-of-the-art knowledge on specific applications

    DĂ©composition en sous bandes pour la compression d'images sans perte par extension de la transformation par arrondi

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    Dans cet article, nous proposons une nouvelle approche utilisant la transformation par arrondi (rounding transform : RT) pour la compression sans perte par décomposition en sous-bandes. Dans ce but, nous définissons une extension de la RT, nommée ORT (overlapping RT). Celle-ci est définie dans le domaine de la transformée en Z, et est utilisée pour développer un systÚme de codage en sous-bandes sans perte. L'idée principale de cette approche est de décomposer la matrice polyphasé du banc de filtres d'analyse en plusieurs matrices de l'ORT. La méthode proposée est plus générale que les propositions antérieures car elle offre de multiples possibilités de mise en oeuvre. Cinq bancs de filtres sont considérés à titre d'exemples et leurs performances sont comparées en terme d'entropie totale dans la compression d'images variées

    Perceptual lossless medical image coding

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    A novel perceptually lossless coder is presented for the compression of medical images. Built on the JPEG 2000 coding framework, the heart of the proposed coder is a visual pruning function, embedded with an advanced human vision model to identify and to remove visually insignificant/irrelevant information. The proposed coder offers the advantages of simplicity and modularity with bit-stream compliance. Current results have shown superior compression ratio gains over that of its information lossless counterparts without any visible distortion. In addition, a case study consisting of 31 medical experts has shown that no perceivable difference of statistical significance exists between the original images and the images compressed by the proposed coder

    A Vlsi architecture for lifting-based wavelet packet transform in fingerprint image compression

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    FBI uses a technique called Wavelet Scalar Quantization (WSQ), a wavelet packet transform (WPT) based method, to compress its fingerprint images. Though many VLSI architectures have been proposed for wavelet transform in the literature, it is not the case for the WPT. In this thesis, a VLSI architecture capable of computing the WPT is presented for application of WSQ. In the proposed architecture, Lifting Scheme (LS) is used to generate wavelets instead of the traditional convolution filter-bank (FB) specified in original standard. A comparative study between LS and FB shows that quality of images transformed by LS is completely acceptable (with 30dB∌40dB PSNR at a target bit rate of 0.75dpp) while fewer operations required. In particular, to compare with FB, the hardware consumption, for our WSQ application, is reduced to half due to the LS. Moreover, this architecture can be easily configured to compute any required WPT application

    Real-time scalable video coding for surveillance applications on embedded architectures

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    Codage d'images avec et sans pertes à basse complexité et basé contenu

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    This doctoral research project aims at designing an improved solution of the still image codec called LAR (Locally Adaptive Resolution) for both compression performance and complexity. Several image compression standards have been well proposed and used in the multimedia applications, but the research does not stop the progress for the higher coding quality and/or lower coding consumption. JPEG was standardized twenty years ago, while it is still a widely used compression format today. With a better coding efficiency, the application of the JPEG 2000 is limited by its larger computation cost than the JPEG one. In 2008, the JPEG Committee announced a Call for Advanced Image Coding (AIC). This call aims to standardize potential technologies going beyond existing JPEG standards. The LAR codec was proposed as one response to this call. The LAR framework tends to associate the compression efficiency and the content-based representation. It supports both lossy and lossless coding under the same structure. However, at the beginning of this study, the LAR codec did not implement the rate-distortion-optimization (RDO). This shortage was detrimental for LAR during the AIC evaluation step. Thus, in this work, it is first to characterize the impact of the main parameters of the codec on the compression efficiency, next to construct the RDO models to configure parameters of LAR for achieving optimal or sub-optimal coding efficiencies. Further, based on the RDO models, a “quality constraint” method is introduced to encode the image at a given target MSE/PSNR. The accuracy of the proposed technique, estimated by the ratio between the error variance and the setpoint, is about 10%. Besides, the subjective quality measurement is taken into consideration and the RDO models are locally applied in the image rather than globally. The perceptual quality is improved with a significant gain measured by the objective quality metric SSIM (structural similarity). Aiming at a low complexity and efficient image codec, a new coding scheme is also proposed in lossless mode under the LAR framework. In this context, all the coding steps are changed for a better final compression ratio. A new classification module is also introduced to decrease the entropy of the prediction errors. Experiments show that this lossless codec achieves the equivalent compression ratio to JPEG 2000, while saving 76% of the time consumption in average in encoding and decoding.Ce projet de recherche doctoral vise Ă  proposer solution amĂ©liorĂ©e du codec de codage d’images LAR (Locally Adaptive Resolution), Ă  la fois d’un point de vue performances de compression et complexitĂ©. Plusieurs standards de compression d’images ont Ă©tĂ© proposĂ©s par le passĂ© et mis Ă  profit dans de nombreuses applications multimĂ©dia, mais la recherche continue dans ce domaine afin d’offrir de plus grande qualitĂ© de codage et/ou de plus faibles complexitĂ© de traitements. JPEG fut standardisĂ© il y a vingt ans, et il continue pourtant Ă  ĂȘtre le format de compression le plus utilisĂ© actuellement. Bien qu’avec de meilleures performances de compression, l’utilisation de JPEG 2000 reste limitĂ©e due Ă  sa complexitĂ© plus importe comparĂ©e Ă  JPEG. En 2008, le comitĂ© de standardisation JPEG a lancĂ© un appel Ă  proposition appelĂ© AIC (Advanced Image Coding). L’objectif Ă©tait de pouvoir standardiser de nouvelles technologies allant au-delĂ  des standards existants. Le codec LAR fut alors proposĂ© comme rĂ©ponse Ă  cet appel. Le systĂšme LAR tend Ă  associer une efficacitĂ© de compression et une reprĂ©sentation basĂ©e contenu. Il supporte le codage avec et sans pertes avec la mĂȘme structure. Cependant, au dĂ©but de cette Ă©tude, le codec LAR ne mettait pas en oeuvre de techniques d’optimisation dĂ©bit/distorsions (RDO), ce qui lui fut prĂ©judiciable lors de la phase d’évaluation d’AIC. Ainsi dans ce travail, il s’agit dans un premier temps de caractĂ©riser l’impact des principaux paramĂštres du codec sur l’efficacitĂ© de compression, sur la caractĂ©risation des relations existantes entre efficacitĂ© de codage, puis de construire des modĂšles RDO pour la configuration des paramĂštres afin d’obtenir une efficacitĂ© de codage proche de l’optimal. De plus, basĂ©e sur ces modĂšles RDO, une mĂ©thode de « contrĂŽle de qualitĂ© » est introduite qui permet de coder une image Ă  une cible MSE/PSNR donnĂ©e. La prĂ©cision de la technique proposĂ©e, estimĂ©e par le rapport entre la variance de l’erreur et la consigne, est d’environ 10%. En supplĂ©ment, la mesure de qualitĂ© subjective est prise en considĂ©ration et les modĂšles RDO sont appliquĂ©s localement dans l’image et non plus globalement. La qualitĂ© perceptuelle est visiblement amĂ©liorĂ©e, avec un gain significatif mesurĂ© par la mĂ©trique de qualitĂ© objective SSIM. Avec un double objectif d’efficacitĂ© de codage et de basse complexitĂ©, un nouveau schĂ©ma de codage LAR est Ă©galement proposĂ© dans le mode sans perte. Dans ce contexte, toutes les Ă©tapes de codage sont modifiĂ©es pour un meilleur taux de compression final. Un nouveau module de classification est Ă©galement introduit pour diminuer l’entropie des erreurs de prĂ©diction. Les expĂ©rimentations montrent que ce codec sans perte atteint des taux de compression Ă©quivalents Ă  ceux de JPEG 2000, tout en Ă©conomisant 76% du temps de codage et de dĂ©codage

    Advanced methods and deep learning for video and satellite data compression

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    L'abstract Ăš presente nell'allegato / the abstract is in the attachmen
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