An algorithm for automatic modelling of wavelet coefficients from context properties is presented. The algorithm is used to implement an image coder, in order to demonstrate its image coding efficiency. The modelling of wavelet coefficients is performed by partitioning the weighted context property space to regions. Each of the regions has a dynamic probability distribution stating the predictions of the modelled coefficients. The coding performance of the algorithm is compared to other efficient wavelet-based image compression methods.