7. The Wavelets Domain

  1. Hans Georg Schaathun

Published Online: 22 AUG 2012

DOI: 10.1002/9781118437957.ch7

Machine Learning in Image Steganalysis

Machine Learning in Image Steganalysis

How to Cite

Schaathun, H. G. (2012) The Wavelets Domain, in Machine Learning in Image Steganalysis, John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9781118437957.ch7

Author Information

  1. Ålesund University College, Norway

Publication History

  1. Published Online: 22 AUG 2012
  2. Published Print: 21 AUG 2012

ISBN Information

Print ISBN: 9780470663059

Online ISBN: 9781118437957

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Keywords:

  • the wavelets domain;
  • wavelet transforms, in digital image processing;
  • machine learning-based steganalysis, from wavelet of images;
  • wavelets' high-level/visual view, and use in image analysis;
  • FWT, discrete wavelet transform implementation;
  • DWT using the Haar wavelet;
  • wavelet transform in Python;
  • HCF in the wavelet domain;
  • denoising algorithms/WAM, noise/prediction error;
  • LAW denoising in wavelet, LAW-ML image optimality

Summary

This chapter contains sections titled:

  • A Visual View

  • The Wavelet Domain

  • Farid's Features

  • HCF in the Wavelet Domain

  • Denoising and the WAM Features

  • Experiment and Comparison