Color filter array interpolation based on spatial adaptivity

Conventional approach in single-chip digital cameras is a use of color lter arrays (CFA) in order to sample dierent spectral components. Demosaicing algorithms interpolate these data to complete red, green, and blue values for each image pixel, in order to produce an RGB image. In this paper we propose a novel demosaicing algorithm for the Bayer CFA. For the algorithm design we assume that the initial interpolation estimates of color channels contain two additive components: the true values of color intensities and the errors. The errors are considered as an additive noise, and often called as a demosaicing noise, that has to be removed. This noise is not white and strongly depends on the signal. Usually, the intensity of this noise is higher near edges of image details. We use specially designed signal-adaptive lter to remove the interpolation errors. This lter is based on the local polynomial approximation (LPA) and the paradigm of the intersection of condence intervals (ICI) applied for selection adaptively varying scales (window sizes) of LPA. The LPA-ICI technique is nonlinear and spatially-adaptive with respect to the smoothness and irregularities of the image. The eciency of the proposed approach is demonstrated by simulation results. Keywords: Bayer pattern, color lter array interpolation, spatially adaptive denoising