Edge-Preserving Integration of a Normal Field: Weighted Least Squares and L1 Approaches
Résumé
We introduce several new functionals, inspired from variational image denoising models, for recovering a piecewise-smooth surface from a dense estimation of its normal field. In the weighted least-squares approach, the non-differentiable elements of the surface are a priori detected so as to weight the least-squares model. To avoid this detection step, we introduce reweighted least-squares for minimising an isotropic TV-like functional, and split-Bregman iterations for L1 minimisation.
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