27 research outputs found

    Gray Scale and Color Medical Image Compression by Lifting Wavelet; Bandelet and Quincunx Wavelets Transforms : A Comparison Study

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    The Quincunx wavelet , the lifting Scheme wavelet and the Second generation bandelet transform are a new method to offer an optimal representation for image geometric; we use this transform to study medical image compressed using the Quincunx transform coupled by SPIHT coder. We are interested in compressed medical image, In order to develop the compressed algorithm we compared our results with those obtained by this transforms application in medical image field. We concluded that the results obtained are very satisfactory for medical image domain. Our algorithm provides very important PSNR and MSSIM values for medical images compression

    State of the art in 2D content representation and compression

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    Livrable D1.3 du projet ANR PERSEECe rapport a été réalisé dans le cadre du projet ANR PERSEE (n° ANR-09-BLAN-0170). Exactement il correspond au livrable D3.1 du projet

    Adapted generalized lifting schemes for scalable lossless image coding

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    International audienceStill image coding occasionally uses linear predictive coding together with multi-resolution decompositions, as may be found in several papers. Those related approaches do not take into account all the information available at the decoder in the prediction stage. In this paper, we introduce an adapted generalized lifting scheme in which the predictor is built upon two filters, leading to taking advantage of all this available information. With this structure included in a multi-resolution decomposition framework, we study two kinds of adaptation based on least squares estimation, according to different assumptions, which are either a global or a local second order stationarity of the image. The efficiency in lossless coding of these decompositions is shown on synthetic images and their performances are compared with those of well-known codecs (S+P, JPEG-LS, JPEG2000, CALIC) on actual images. Four images' families are distinguished: natural, MRI medical, satellite and textures associated with fingerprints. On natural and medical images, the performances of our codecs do not exceed those of classical codecs. Now for satellite images and textures, they present a slightly noticeable (about 0.05 to 0.08 bpp) coding gain compared to the others that permit a progressive coding in resolution, but with a greater coding time

    Improved local pdf estimation in the wavelet domain for generalized lifting

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    Generalized Lifting (GL) has been studied for lossy image compression in [2,3]. It has been demonstrated that the method leads to a significant reduction of the wavelet coefficients energy and entropy. The definition of the GL relies on an estimation of the pdf of the pixel to encode conditioned to a surrounding context. The objective of this paper is to present an improved method for the estimation of the pdf at the local level. Rather than assuming that the local pdf is monomodal, symmetric, and centered at the central value of the best context match within a neighborhood, as in [3], we follow the idea of self similarity proposed in [1] for denoising, and propose to estimate the pdf using all the causal contexts within a window. Therefore, all the available knowledge about the neighborhood is incorporated. No assumptions about the characteristics of the pdf are made. A generalized lifting operator that minimizes the energy is applied to each context during the encoding process. Experimental results show an important increment in the energy and entropy gains when compared to previous strategies [2,3].Postprint (published version

    Adaptive polyphase subband decomposition structures for image compression

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    Cataloged from PDF version of article.Subband decomposition techniques have been extensively used for data coding and analysis. In most filter banks, the goal is to obtain subsampled signals corresponding to different spectral regions of the original data. However, this approach leads to various artifacts in images having spatially varying characteristics, such as images containing text, subtitles, or sharp edges. In this paper, adaptive filter banks with perfect reconstruction property are presented for such images. The filters of the decomposition structure which can be either linear or nonlinear vary according to the nature of the signal. This leads to improved image compression ratios. Simulation examples are presented

    Adaptive lifting schemes with a global L1 minimization technique for image coding

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    International audienceMany existing works related to lossy-to-lossless image compression are based on the lifting concept. In this paper, we present a sparse op- timization technique based on recent convex algorithms and applied to the prediction filters of a two-dimensional non separable lifting structure. The idea consists of designing these filters, at each resolution level, by minimizing the sum of the â„“1-norm of the three detail subbands. Extending this optimization method in order to perform a global minimization over all resolution levels leads to a new opti- mization criterion taking into account linear dependencies between the generated coefficients. Simulations carried out on still images show the benefits which can be drawn from the proposed optimization techniques

    Two-dimensional non separable adaptive lifting scheme for still and stereo image coding

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    International audienceMany existing works related to lossy-to-lossless image compression are based on the lifting concept. However, it has been observed that the separable lifting scheme structure presents some limitations because of the separable processing performed along the image lines and columns. In this paper, we propose to use a 2D non separable lifting scheme decomposition that enables progressive reconstruction and exact decoding of images. More precisely, we focus on the optimization of all the involved decomposition operators. In this respect, we design the prediction filters by minimizing the variance of the detail signals. Concerning the update filters, we propose a new optimization criterion which aims at reducing the inherent aliasing artefacts. Simulations carried out on still and stereo images show the benefits which can be drawn from the proposed optimization of the lifting operators
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