@INPROCEEDINGS{7351750,
  author={J. {Frecon} and N. {Pustelnik} and H. {Wendt} and P. {Abry}},
  booktitle={2015 IEEE International Conference on Image Processing (ICIP)}, 
  title={Multivariate optimization for multifractal-based texture segmentation}, 
  year={2015},
  volume={},
  number={},
  pages={4957-4961},
  abstract={This work aims to segment a texture into different regions, each characterized by a priori unknown multifractal properties. The multifractal properties are quantified using the multiscale function C1,j that quantifies the evolution along analysis scales 2j of the empirical mean of the log of the wavelet leaders. The segmentation procedure is applied to local estimate of C1,j. It involves a multivariate Mumford-Shah relaxation formulated as a convex optimization problem involving a structure tensor penalization and an efficient algorithmic solution based on primal-dual proximal algorithm. The performances are evaluated on synthetic textures.},
  keywords={convex programming;fractals;image segmentation;image texture;tensors;wavelet transforms;multivariate optimization;multifractal-based texture segmentation;synthetic textures;primal-dual proximal algorithm;structure tensor penalization;convex optimization problem;multivariate Mumford-Shah relaxation;wavelet leaders;multiscale function;Fractals;Image segmentation;Convex functions;Tensile stress;Algorithm design and analysis;Biomedical measurement;Wavelet analysis;Local regularity;multifractal spectrum;segmentation;convex optimization;wavelet Leaders},
  doi={10.1109/ICIP.2015.7351750},
  ISSN={},
  month={Sep.},}