Hyperspectral pan-sharpening: a variational convex constrained formulation to impose parallel level lines, solved with ADMM

In this paper, we address the issue of hyperspectral pan-sharpening, which consists in fusing a (low spatial resolution) hyperspectral image HX and a (high spatial resolution) panchromatic image P to obtain a high spatial resolution hyperspectral image. The problem is addressed under a variational convex constrained formulation. The objective favors high resolution spectral bands with level lines parallel to those of the panchromatic image. This term is balanced with a total variation term as regularizer. Fit-to-P data and fit-to-HX data constraints are effectively considered as mathematical constraints, which depend on the statistics of the data noise measurements. The developed Alternating Direction Method of Multipliers (ADMM) optimization scheme enables us to solve this problem efficiently despite the non differentiabilities and the huge number of unknowns.Comment: 4 pages, detailed version of proceedings of conference IEEE WHISPERS 201

An Assignment Model with Divorce and Remarriage

We develop a two-sided matching model with positive sorting, divorce and remarriage. Match quality for each couple is revealed ex post and those with poor draws divorce. Competition determines lifetime expected utilities but per-period utilities depend on the laws that govern the distribution of assets upon divorce. We discuss separately cases in which remarriage is or is not feasible and cases in which commitments are or are not made. In all cases, lifetime utilities are exactly pinned down by equilibrium (stability) requirements. Moreover, ex-post Nash bargaining and ex-ante commitment yield the same non-contingent intertemporal allocations. We then analyze the impact of changes in the property division upon divorce, considering for instance a reform that favors women. The short-term impact of the reform on the allocations of already married wives is positive. However, its long-term impact on yet unmarried women is not because such a reform generates lower utility for women within marriage which exactly offsets their higher prospective divorce settlement. When remarriage is possible, more complex effects could occur: the reform typically alters divorce probabilities and it may affect the total surplus generated by marriage, thus either increasing both spouses' welfare or decreasing both.matching, intra-household allocations, Becker-Coase theorem

Light and Chemical Energy

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Investment in Schooling and the Marriage Market

We produce a model with pre-marital schooling investment, endogenuos marital matching and spousal specialization in homework and market production Pre-marital investments generate two kinds of returns: a labor-market return due to the education premium and a marriage-market return because education can improve the intra-marital share of the surplus one can extract from marriage. When the returns to education are gender neutral, men and women educate in equal proportions and there is pure positive assortative matching in the marriage markets. But if the returns are not gender neutral, then there is mixing in equilibrium where some educated individuals marry uneducated spouses and those who educate less because their labor-market return is lower extract a relatively larger share of the marital surplus. Conditional on the choice of schooling, couples’ career decisions affect the size of their marital surplus, but the existence of large and frictionless marriage markets can still produce efficient household specialization where the higher-wage spouse specializes in market production and the lower-wage spouse engages in homework. Even when cultural and social norms or the time requirements of homework dictate that wives devote relatively more time to homework, women can acquire more schooling than men if a gender wage gap exists but narrows with the level of education.

Variable density sampling based on physically plausible gradient waveform. Application to 3D MRI angiography

Performing k-space variable density sampling is a popular way of reducing scanning time in Magnetic Resonance Imaging (MRI). Unfortunately, given a sampling trajectory, it is not clear how to traverse it using gradient waveforms. In this paper, we actually show that existing methods [1, 2] can yield large traversal time if the trajectory contains high curvature areas. Therefore, we consider here a new method for gradient waveform design which is based on the projection of unrealistic initial trajectory onto the set of hardware constraints. Next, we show on realistic simulations that this algorithm allows implementing variable density trajectories resulting from the piecewise linear solution of the Travelling Salesman Problem in a reasonable time. Finally, we demonstrate the application of this approach to 2D MRI reconstruction and 3D angiography in the mouse brain.Comment: IEEE International Symposium on Biomedical Imaging (ISBI), Apr 2015, New-York, United State

Are Intra-Household Allocations Policy Neutral? Theory and Empirical Evidence

We develop a collective household model with spousal matching in which there exists marital gains to assortative matching and marriage quality for each couple is revealed ex post. Changes in alimony laws are shown to affect existing couples and couples-to-be differently. For existing couples, legislative changes that favor (wo)men benefit them especially if the marriage match quality is low, while, for couples not yet formed, they generate offsetting intra-household transfers and lower intra-marital allocations for the spouses who are the intended beneficiary. We then estimate the effect of granting alimony rights to cohabiting couples in Canada using a triple-difference framework since each province extended these rights in different years and requiring different cohabitation length. We find that obtaining the right to petition for alimony led women to lower their labor force participation. These results, however, do not hold – and, in some cases, are reversed – for newly formed cohabiting couples.intra-household allocations, matching, cohabitation, alimony laws

Approximation et Estimation des Opérateurs de Flou Variable

Restoring images degraded by spatially varying blur is a problem encountered in many disciplines such as astrophysics, computer vision or biomedical imaging. Blurring operators are modelled using integral operators with some regularity and decrease conditions on the kernel. Recently, we studied the approximation of these operators in wavelet bases in which operators are highly compressible. They also allow to fastly compute matrix-vector products with a complexity $O(N\epsilon^{-d/M})$ for a precision $\epsilon$ in spectral norm, where N is the number of pixels of a d-dimensional image and M describes the kernel regularity. Additionnaly, we have shown that the sparsity pattern of the matrix can be pre-defined. We exploit these results to study the estimation/reconstruction of the operator from the knwoledge of few point spread functions located at arbitrary positions in the image domain. We propose an original formulation directly in the wavelet domain and a fast algorithm

Iterative Discretization of Optimization Problems Related to Superresolution

International audienceWe study an iterative discretization algorithm for solving optimization problems regularized by the total variation norm over the space M(Ω) of Radon measures on a bounded subset Ω of R d. Our main motivation to study this problem is the recovery of sparse atomic measures from linear measurements. Under reasonable regularity conditions, we arrive at a linear convergence rate guarantee