
doi: 10.1137/060671814
This paper focuses on the problem of multiplicative noise removal. We draw our inspiration from the modeling of speckle noise. By using a MAP estimator, we can derive a functional whose minimizer corresponds to the denoised image we want to recover. Although the functional is not convex, we prove the existence of a minimizer and we show the capability of our model on some numerical examples. We study the associated evolution problem, for which we derive existence and uniqueness results for the solution. We prove the convergence of an implicit scheme to compute the solution.
multiplicative noise, [INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV], Calculus of variation, speckle noise, image restoration., $BV$, variational approach, [MATH.MATH-AP] Mathematics [math]/Analysis of PDEs [math.AP], image restoration, functional analysis
multiplicative noise, [INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV], Calculus of variation, speckle noise, image restoration., $BV$, variational approach, [MATH.MATH-AP] Mathematics [math]/Analysis of PDEs [math.AP], image restoration, functional analysis
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