AM-FM image filters

We introduce a multicomponent invertible AM-FM image transform and use it to define new nonlinear AM-FM filters for performing modulation domain image processing. The key elements of the transform are analysis and synthesis filterbanks based on the steerable image pyramid and perfect reconstruction demodulation algorithms based on analytic differentiation of continuous cubic tensor spline models fit to the unwrapped phase samples of a digital image. We demonstrate spatially and spectrally localized orientation and frequency selective filtering, simple image restoration, and image fusion in the modulation domain. These results are also among the first to demonstrate high fidelity image reconstructions from computed multicomponent AM-FM models.