Frédéric Champagnat

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Super-resolution (SR) techniques make use of subpixel shifts between frames in an image sequence to yield higher resolution images. We propose an original observation model devoted to the case of nonisometric inter-frame motion as required, for instance, in the context of airborne imaging sensors. First, we describe how the main observation models used in(More)
—This paper provides a complete characterization of stationary Markov random fields on a finite rectangular (non-toroidal) lattice in the basic case of a second-order neighborhood system. Equivalently, it characterizes stationary Markov fields on 2 whose restrictions to finite rectangular subsets are still Markovian (i.e., even on the boundaries). Until(More)
Robust estimation of the optical flow is addressed through a multiresolution energy minimization. It involves repeated evaluation of spatial and temporal gradients of image intensity which rely usually on bilinear interpolation and image filtering. We propose to base both computations on a single pyramidal cubic B-spline model of image intensity. We show(More)
We consider the recovery of 1-D image features. Such features can be described by a noisy, blurred and undersam-pled image of a unique 1-D profile. The profile's recovery is modeled as a 1-D continuous super-resolution (SR) problem. We adopt a functional estimation within a Tikhonov regularization framework. A linear closed-form solution is derived and(More)
We present a super-resolution (SR) color freeze frame of small moving objects in video sequences. In the last two decades, all SR methods except one focus on the case of rigid scene. We propose a fast and robust method that performs SR reconstruction on tracked objects. After an affine registration of the regions of interest of objects, a non-uniform(More)