IEEE Trans Image Process - Incorporating patch subspace model in Mumford-Shah type active contours.

Tópicos

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Resumo

In this paper, we propose a unified energy minimization model for segmentation of non-smooth image structures, e.g., textures, based on Mumford-Shah functional and linear patch model. We consider that image patches of a non-smooth image structure can be modeled by a patch subspace, and image patches of different non-smooth image structures belong to different patch subspaces, which leads to a computational framework for segmentation of non-smooth image structures. Motivated by the Mumford-Shah model, we show that this segmentation framework is equivalent to minimizing a piecewise linear patch reconstruction energy. We also prove that the error of segmentation is bounded by the error of the linear patch reconstruction, meaning that improving the linear patch reconstruction for each region leads to reduction of the segmentation error. In addition, we derive an algorithm for the linear patch reconstruction with proven global optimality and linear rate of convergence. The segmentation in our method is achieved by minimizing a single energy functional without requiring predefined features. Hence, compared with the previous methods that require predefined texture features, our method can be more suitable for handling general textures in unsupervised segmentation. As a by-product, our method also produces a dictionary of optimized orthonormal descriptors for each segmented region. We mainly evaluate our method on the Brodatz textures. The experiments validate our theoretical claims and show the clear superior performance of our methods over other related methods for segmentation of the textures.

Resumo Limpo

paper propos unifi energi minim model segment nonsmooth imag structur eg textur base mumfordshah function linear patch model consid imag patch nonsmooth imag structur can model patch subspac imag patch differ nonsmooth imag structur belong differ patch subspac lead comput framework segment nonsmooth imag structur motiv mumfordshah model show segment framework equival minim piecewis linear patch reconstruct energi also prove error segment bound error linear patch reconstruct mean improv linear patch reconstruct region lead reduct segment error addit deriv algorithm linear patch reconstruct proven global optim linear rate converg segment method achiev minim singl energi function without requir predefin featur henc compar previous method requir predefin textur featur method can suitabl handl general textur unsupervis segment byproduct method also produc dictionari optim orthonorm descriptor segment region main evalu method brodatz textur experi valid theoret claim show clear superior perform method relat method segment textur

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