title: Image modeling using interscale phase properties of complex wavelet coefficients.
abstract: This paper describes an approach to image modelling using interscale phase relationships of wavelet coefficients for use in image estimation applications. The method is based on the dual tree complex wavelet transform, but a phase rotation is applied to the coefficients to create complex "derotated" coefficients. These derotated coefficients are shown to have increased correlation compared to standard wavelet coefficients near edge and ridge features allowing improved signal estimation in these areas. The nature of the benefits brought by the derotated coefficients are analyzed and the implications for image estimation algorithm design noted. The observations and conclusions provide a basis for design of the denoising algorithm in [1].
authors.affiliation: Signal Processing and Communications Group, Department of Engineering, University of Cambridge, Cambridge, UK. m.a.miller.02@cantab.net
authors.forename: Mark
authors.initials: M
authors.lastname: Miller
authors.forename: Nick
authors.initials: N
authors.lastname: Kingsbury
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D008962:Models, Theoretical; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity