Modulation models for image processing and wavelet-based image demodulation
AM-FM modulation models for two- and higher-dimensional complex-valued nonstationary signals and images that are locally coherent but globally wideband are studied. Demodulation techniques are studied for demodulating both one-component and multicomponent signals. For the case of multicomponent signals immersed in noise, the individual components must be isolated by spectrally localized multiband filtering prior to demodulation. An algorithm for demodulating the filtered signal components is developed using a quasi-eigenfunction approximation, and bounds for the approximation error are given. After multiband filtering with Gabor wavelets, the filtered demodulation algorithm is used to estimate the dominant emergent frequencies of multicomponent images.<<ETX>>