Jean-François Giovannelli

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The paper deals with the construction of images from visibilities acquired using aperture synthesis instruments: Fourier synthesis, deconvolution, and spectral interpolation/extrapolation. Its intended application is to specific situations in which the imaged object possesses two superimposed components: (i) an extended component together with (ii) a set of(More)
Modern ultrasound Doppler systems are facing the problem of processing increasingly shorter data sets. Spectral analysis of the strongly nonstationary Doppler signal needs to shorten the analysis window while maintaining a low variance and high resolution spectrum. Color flow imaging requires estimation of the Doppler mean frequency from even shorter(More)
There is a need to precisely measure concentration of proteins in biological substance for early diagnosis of disease or knowledge of fundamental biological processes. Many apparatus have been proposed, and now data processing methods have to be investigated. This paper focuses on data processing of proteomic experiments combining nano liquid chromatography(More)
[1] J.-F. Giovannelli, J. Idier, G. Desodt et D. Muller, Regularized adaptive long autoregressive spectral analysis , IEEE Trans. Geosci. Remote Sensing , vol. 39, n◦10, pp. 2194 2202, octobre 2001. [2] P. Ciuciu, J. Idier et J.-F. Giovannelli, Regularized estimation of mixed spectra using a circular GibbsMarkov model , IEEE Trans. Signal Processing , vol.(More)
Autoregressive (AR) modelling has already been proposed as an alternative to fast Fourier transform to process ultrasound (US) Doppler signals. Previous works introduced long AR models, set up under a regularization framework. The latter may be in 1-D (frequency) or 2-D (frequency and space or time). This study generalizes the spectrum regularization in the(More)
The paper tackles the problem of joint deconvolution and segmentation specifically for textured images. The images are composed of patches of textures that belong to a set of K possible classes. Each class of image is described by a Gaussian random field and the classes are modelled by a Potts field. The method relies on a hierarchical model and a Bayesian(More)
9 This paper is a synthetic overview of regularization, maximum entropy and probabilistic methods for some inverse problems such as deconvolution and Fourier synthesis problems which arise in mass spectrometry. First we present a unified description of such problems and discuss the reasons why simple naı̈ve methods cannot give satisfactory results. Then we(More)
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