Texture Oriented Image Inpainting based on Local Statistical Model

J. Grim, P. Somol, P. Pudil, I. Míková, and M. Malec (Czech Republic)


Image Restoration, Image Inpainting, Color Texture Pre diction, Local Texture Model, Gaussian Mixtures, EM Al gorithm.


Image inpainting as a means of substituting missing image parts can become difficult when the image is textured. In this paper we apply a local statistical model of the source color image with the aim to predict missing texture regions. We have shown in a series of papers that textures can be modeled locally by estimating the joint probability density of spectral pixel values in a suitably chosen observation window. For the sake of image inpainting we estimate the joint multivariate density in the form of a Gaussian mixture of product components. The missing image region is in painted iteratively by step-wise prediction of the unknown spectral values.

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