Inverse problem formulation for regularity estimation in images - Archive ouverte HAL Access content directly
Conference Papers Year : 2014

Inverse problem formulation for regularity estimation in images


The identification of texture changes is a challenging problem that can be addressed by considering local regularity fluctuations in an image. This work develops a procedure for local regularity estimation that combines a convex optimization strategy with wavelet leaders, specific wavelet coefficients recently introduced in the context of multifractal analysis. The proposed procedure is formulated as an inverse problem that combines the joint estimation of both local regularity exponent and of the optimal weights underlying regularity measurement. Numerical experiments using synthetic texture indicate that the performance of the proposed approach compares favorably against other wavelet based local regularity estimation formulations. The method is also illustrated with an example involving real-world texture.
Fichier principal
Vignette du fichier
pustelnik_15172.pdf (275.4 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-01399871 , version 1 (21-11-2016)


  • HAL Id : hal-01399871 , version 1
  • OATAO : 15172


Nelly Pustelnik, Patrice Abry, Herwig Wendt, Nicolas Dobigeon. Inverse problem formulation for regularity estimation in images. International Conference on Image Processing (ICIP 2014), Oct 2014, Paris, France. pp. 6081-6085. ⟨hal-01399871⟩
99 View
114 Download


Gmail Facebook X LinkedIn More