A self-consistent wavelet method for denoising images with missing pixels

In this work, we consider the problem of wavelet image denoising when some of the pixel values are unobserved. Our approach is to treat those unobserved pixels as missing data and adopt the self-consistency principle to define a "best" wavelet estimate for the true image. We propose fast and effective algorithms for computing such a self-consistent wavelet estimate. The practical performance of our proposal is evaluated via a simulation study. A possible application of this work is image inpainting.

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