Title :
Tests of Gaussianity and linearity for random fields using estimated higher order spectra
Author_Institution :
Dept. of Math., Univ. of Manchester Inst. of Sci. & Technol., UK
fDate :
1/1/1998 12:00:00 AM
Abstract :
We present frequency domain tests of Gaussianity and linearity for random fields and study their power both analytically and by simulation. Our tests conform to the likelihood ratio principle, and the test statistics (chi-squared in both cases) are simple and intuitively plausible. Using these tests, we found certain texture images to be both non-Gaussian and nonlinear
Keywords :
Gaussian processes; frequency-domain analysis; higher order statistics; image texture; maximum likelihood estimation; random processes; spectral analysis; Gaussianity tests; chi-squared statistics; estimated higher order spectra; frequency domain tests; likelihood ratio principle; linearity tests; multidimensional signal processing; nonGaussian images; nonlinear images; random fields; simulation; test statistics; texture images; Analytical models; Frequency domain analysis; Frequency estimation; Gaussian processes; Higher order statistics; Linearity; Spectral analysis; Statistical analysis; Stochastic processes; Testing;
Journal_Title :
Signal Processing, IEEE Transactions on
