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Image deblurring is essential in high resolution imaging, e.g., astronomy, microscopy or computational photography. Shift-invariant blur is fully characterized by a single point-spread-function (PSF). Blurring is then modeled by a convolution, leading to efficient algorithms for blur simulation and removal that rely on fast Fourier transforms. However, in(More)
To investigate if the characteristics of human intestinal Escherichia coli are changing with the environment of the host, we studied intestinal E. coli from subjects having recently migrated from a temperate to a tropical area. We determined the phylogenetic group, the prevalence of the antibiotic resistance, the presence of integrons and the strain(More)
We propose a compositional model for predicting the reflectance and the transmittance of multilayer specimens composed of layers having possibly distinct refractive indices. The model relies on the laws of geometrical optics and on a description of the multiple reflection-transmission of light between the different layers and interfaces. The highly complex(More)
Tomographic iterative reconstruction methods need a very thorough modeling of data. This point becomes critical when the number of available projections is limited. At the core of this issue is the projector design, i.e., the numerical model relating the representation of the object of interest to the projections on the detector. Voxel driven and ray driven(More)
—Data modelization in tomography is a key point for iterative reconstruction. The design of the projector, i.e. the numerical model of projection, is mostly influenced by the representation of the object of interest, decomposed on a discrete basis of functions. Standard projector models are voxel or ray driven; more advanced models such as distance driven,(More)
This article provides a theoretical junction between two different mathematical models dedicated to the reflectance and the transmittance of diffusing layers. The Kubelka-Munk model proposes a continuous description of scattering and absorption for two opposite diffuse fluxes in a homogenous layer (continuous 2-flux model). On the other hand, Kubelka's(More)
This paper provides a theoretical connection between two different mathematical models dedicated to the reflectance and the transmittance of diffusing layers. The Kubelka–Munk model proposes a continuous description of scattering and absorption for two opposite diffuse fluxes in a homogeneous layer (continuous two-flux model). On the other hand, Kubelka's(More)
— Hough Transform (H.T.) is a classical tool for multiple alignment detection in image processing, based on the property that Aligned Points are transformed into Intersecting Curves (APIC). Among the alternative transforms which possess the APIC property, one of the most interesting is Polar Transform (P.T.) which exchanges a point (a,b) and the straight(More)
Several problems in signal processing and machine learning can be casted as optimization problems. In many cases, they are of large-scale, nonlinear, have constraints, and may be nonsmooth in the unknown parameters. There exists plethora of fast algorithms for smooth convex optimization, but these algorithms are not readily applicable to nonsmooth problems,(More)