Classification between natural and graphics images based on generalized Gaussian distributions

Atsushi Morinaga, Kenji Hara, Kohei Inoue, Kiichi Urahama

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

We propose a novel method for classifying photographic and computer-generated images based on generalized Gaussian distribution (GGD) modeling of subband coefficients. The estimated shape and standard deviation parameters of GGD within each resolution level, the ratio of the estimated shape parameters between different resolution levels, and the ratio of the estimated standard deviation parameters between different resolution levels are used as features for the classification.

Original languageEnglish
Pages (from-to)31-34
Number of pages4
JournalInformation Processing Letters
Volume138
DOIs
Publication statusPublished - Oct 2018

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Signal Processing
  • Information Systems
  • Computer Science Applications

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