Image texture characterization using the discrete orthonormal S-transform.
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.
Drabycz
Sylvia
S
Department of Electrical and Computer Engineering, University of Calgary, 2500 University Dr NW, Calgary, Alberta, T2N 1N4, Canada.
Stockwell
Robert G
RG
Mitchell
J Ross
JR
D000465:Algorithms; D016477:Artifacts; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D003952:Diagnostic Imaging / Q000295:instrumentation / Q000379:methods; D005583:Fourier Analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated; D011856:Radiographic Image Enhancement; D014057:Tomography, X-Ray Computed / Q000379:methods