Image Modeling Using Interscale Phase Properties of Complex Wavelet Coefficients

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 de- noising algorithm in [1].