In this thesis, we focus on the restoration of three-dimensional image of fluorescence microscopy. Two major difficulties in this imaging system are considered. The first one is the depth-variant blur due to aberrations induced by the refractive index variation in the optical system and the imaged specimen. The second difficulty is the noise due to the photon counting process. The goal of this thesis is to reduce these distortions in order to provide biologists with a better image quality. In the first part of this thesis, we study the approximation models of the depth-variant blur and choose an appropriate model for the inversion problem. In that model, the depth-variant point spread function (PSF) is approximated by a convex combination of a set of space-invariant PSFs. We then develop for that model two fast non-blind restoration methods by minimizing a regularized criterion, each of these methods is adapted to the type of noise present in images of confocal or wide field microscopy. In the second part, we address the problem of blind restoration and propose two methods where the depth-variant blur and the image are jointly estimated. In the first method, the PSF is estimated at each voxel in the considered volume in order to allow high degree of freedom on the PSF shape while in the second method, the shape of the PSF is constrained by a Gaussian function in order to reduce the number of unknown variables and the space of possible solutions. In both blind estimation methods, the effect of optical aberrations is not effectively estimated due to the lack of information. We thus improve these estimation methods by alternating some constraints in the frequency and spatial domains. Results on simulated and real data are shown.
