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In this paper, we propose a method to simultaneously separate and reconstruct the physical components of an object observed in the context of spectral Computed Tomography (CT). Spectral CT has been made possible thansk to the technological breakthrough of X-ray hybrid pixel detectors in the last years and brings CT imaging from an anatomic to a functional biomedical imaging modality. Our contribution...
Cone Beam Computerized Tomography (CBCT) and Positron Emission Tomography (PET) Scans are medical imaging devices that require solving ill-posed inverse problems. The models considered come directly from the physics of the acquisition devices, and take into account the specificity of the (Poisson) noise. We propose various fast numerical schemes to compute the solution. In particular, we show that...
In this paper we address the problem of scalable video indexing. We propose a new framework combining sparse spatial multiscale patches and Group of Pictures (GoP) motion patches. The distributions of these sets of patches are compared via the Kullback-Leibler divergence estimated in a non-parametric framework using a k-th Nearest Neighbor (kNN) estimator. We evaluated this similarity measure on selected...
In this paper, we define a similarity measure between images in the context of (indexing and) retrieval. We use the Kullback-Leibler (KL) divergence to compare sparse multiscale image representations. The KL divergence between parameterized marginal distributions of wavelet coefficients has already been used as a similarity measure between images. Here we use the Laplacian pyramid and consider the...
In this paper, we define a similarity measure to compare images in the context of (indexing and) retrieval. We use the Kullback-Leibler (KL) divergence to compare sparse multiscale image descriptions in a wavelet domain. The KL divergence between wavelet coefficient distributions has already been used as a similarity measure between images. The novelty here is twofold. Firstly, we consider the dependencies...
We present a new method for component separation from multi-frequency maps aimed to extract Sunyaev–Zeldovich (SZ) galaxy clusters from cosmic microwave background (CMB) experiments. This method is best suited to recover non-Gaussian, spatially localized and sparse signals. We apply our method on simulated maps of the ACBAR experiment. We find that this method improves the reconstruction of the integrated...
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