A wavelet-based multiresolution statistical model for texture

A multiresolution statistical model, consisting of random fields in wavelet subbands, is proposed for texture, and has produced promising results in texture synthesis experiments. The basic idea here is that a complex random field model, e.g., one that contains long-range and nonlinear spatial correlations, can be constructed from several simpler ones.

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