Web projektu DAR

Research Centre
Data - Algorithms - Decision Making

Established in 2005 under support of MŠMT ČR (project 1M0572)

Publications

Texture Oriented Image Inpainting based on Local Statistical Model

Typ:

Conference paper

Authors:

Grim J., Somol P., Pudil P., Míková I., Malec M.

Proceedings name:

Proc. 10th IASTED Conf. on Signal & Image Processing, SIP 2008

Publisher:

ACTA Press

Serie:

Calgary

Year:

2008

Contact:

Ing. Jiří Grim, CSc. (ÚTIA - Oddělení rozpoznávání obrazů)

Keywords:

Image Restoration, Image Inpainting, Color Texture Predictio

Anotation:

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 inpainted iteratively by step-wise prediction of the unknown spectral values.