We study the amount of information that is contained in “random pictures” by which we mean the sample sets of a Boolean model. To quantify the notion “amount of information” two closely connected questions are investigated: on the one hand, we study the probability that a large number of balls is needed for a full reconstruction of a Boolean model sample set. On the other hand, we study the quantization error of the Boolean model w.r.t. the Hausdorff distance as a distortion measure.

Original languageEnglish
Pages (from-to)133-161
Number of pages29
JournalJournal of Complexity
Volume53
DOIs
StatePublished - Aug 2019

    Scopus subject areas

  • Control and Optimization
  • Applied Mathematics
  • Mathematics(all)
  • Numerical Analysis
  • Algebra and Number Theory
  • Statistics and Probability

    Research areas

  • Boolean model, Functional quantization, High resolution quantization, Information based complexity, Metric entropy, DIFFUSION-PROCESSES, CODING COMPLEXITY, QUADRATURE, FUNCTIONAL QUANTIZATION, CONSTRUCTIVE QUANTIZATION

ID: 35797721