Abstract-A test for isotropy of images modeled as stationary or intrinsically stationary random fields on a lattice is developed. The test is based on wavelet theory, and can operate on the horizontal and vertical scale of choice, or on any combination of scales. Scale is introduced through the wavelet variances (sometimes called the wavelet power spectrum), which decompose the variance over different horizontal and vertical spatial scales. The method is more general than existing tests for isotropy, since it handles intrinsically stationary random fields as well as second-order stationary fields. The performance of the method is demonstrated on samples from different random fields, and compared with three existing methods. It is competitive with or outperforms existing methods since it consistently rejects close to the nominal level for isotropic fields while having a rejection rate for anisotropic fields comparable with the existing methods in the stationary case, and superior in the intrinsic case. As practical examples, paper density images of handsheets and mammogram images are analyzed. Index Terms-Maximal overlap discrete wavelet transform, wavelet variance, isotropy, anisotropy, random fields.
Thon et al. REF developed a multiscale wavelet features to represent the isotropy of stationary random fields on a regular lattice.
A Multiscale Wavelet-Based Test for Isotropy of Random Fields on a Regular Lattice
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Computer Science Mathematics Medicine