M. Monserrat Rincon-Camacho

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Multi-scale total variation models for image restoration are introduced. The models utilize a spatially dependent regularization parameter in order to enhance image regions containing details while still sufficiently smoothing homogeneous features. The fully automated adjustment strategy of the regularization parameter is based on local variance estimators.(More)
A total variation (TV) model with an L 1-fidelity term and a spatially adapted regularization parameter is presented in order to reconstruct images contaminated by impulse noise. This model intends to preserve small details while homogeneous features still remain smooth. The regularization parameter is locally adapted according to a local expected absolute(More)
We study the fixed-point equation, given for a fixed l > 0 by: x = h(1 − |2x − 1| l), x, h ∈ R, where |2x − 1| = |x− 1 2 | 1 2 represents the relative distance of x to the mean value of 0 and 1 which are the fixed points of multiplication. The particular cases l = 1 and 2 are classical. This work intends to look at the question: " How much of the specific(More)
We study the fixed-point equation, given for fixed l > 0 by: where |y| represents the absolute distance of y to 0. Eq. (1.1) induces a duality between 0 and 1, elements of Z 2. We indicate that this duality can be interpreted, in the context of logic, as a paradox. We analyse the theoretical behaviour for l ∈ N * and the experimental results for 0 < l < 1.(More)
SUMMARY We study the fixed-point equation, given for a fixed ν > 0 by: x = h(1 − |2x − 1| ν), x, h ∈ R, where |2x − 1| = |x− 1 2 | 1 2 represents the relative distance of x to the mean value of 0 and 1. The particular cases ν = 1 and 2 are classical. This work looks at the question: " How much of the specific behaviour for ν = 1 and 2 remains valid when the(More)