Image texture characterization using the discrete orthonormal S-transform

Sylvia Drabycz, Robert G. Stockwell, J. Ross Mitchell

Research output: Contribution to journalArticlepeer-review

78 Scopus citations


We present a new efficient approach for characterizing image texture based on a recently published discrete, orthonormal space-frequency transform known as the DOST. We develop a frequency-domain implementation of the DOST in two dimensions for the case of dyadic frequency sampling. Then, we describe a rapid and efficient approach to obtain local spatial frequency information for an image and show that this information can be used to characterize the horizontal and vertical frequency patterns in synthetic images. Finally, we demonstrate that DOST components can be combined to obtain a rotationally invariant set of texture features that can accurately classify a series of texture patterns. The DOST provides the computational efficiency and multi-scale information of wavelet transforms, while providing texture features in terms of Fourier frequencies. It outperforms leading wavelet-based texture analysis methods.

Original languageEnglish (US)
Pages (from-to)696-708
Number of pages13
JournalJournal of Digital Imaging
Issue number6
StatePublished - Dec 2009


  • 3D texture mapping
  • 3D wavelet transform
  • Algorithms
  • Biomedical image analysis
  • Brain imaging
  • Computer assisted detection
  • Computer-aided diagnosis (CAD)
  • Fourier analysis
  • Image analysis
  • Image processing
  • MR imaging
  • Magnetic resonance imaging

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Computer Science Applications


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