Characterization of Self-Similar Multifractals with Wavelet Maxima

Abstract

Self-similar multifractals have a wavelet transform whose maxima define self-similar curves in the scale-space plane. We introduce an algorithm that recovers that affine self-similarity parameters through a voting procedure in the corresponding parameter space. The voting approach is robust with respect to renormalization noises and can recover the value of parameters having random fluctuations. We describe numerical applications to Cantor measures, dyadique multifractals and to the study of Diffusion Limited Aggregates.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1993
Accession Number
AD1020210

Entities

People

  • Stephane Mallat
  • Wen-liang Hwang

Organizations

  • Courant Institute of Mathematical Sciences, NYU

Tags

Communities of Interest

  • Air Platforms
  • C4I

DTIC Thesaurus Topics

  • Algorithms
  • Diffusion
  • Mathematics
  • Wavelet Transforms

Fields of Study

  • Physics

Readers

  • Image Processing and Computer Vision.
  • Mathematical Modeling and Probability Theory.
  • Statistical inference.

Technology Areas

  • Space