Image Interpolation Based on Multi Scale Gradients

Most low-cost consumer grade digital camera systems are currently designed to sense only one color component per image pixel and interpolate the other missing color components (at each pixel)duringreconstruction. The sensing process, which employs aColor Filter Array (CFA), maps each pixel to a single color based on a color pattern. The CFA color pattern and the interpolation process (widely known as demosaicing) have a significant impact on the quality of the reconstructed image. In this paper, A directional CFA interpolation method that is based on multiscale color gradients. The method is easy to implement since it does not make any hard decision, noniterative and threshold free. This method, the horizontal and vertical color difference estimates are blended based on the ratio of the total absolute values of vertical and horizontal color difference gradients over a local window. Method is applied to Bayer and Lukac pattern with great results which shows that the relationship between gradients at different scales can be a very effective feature to optimally combine directional estimates. Result can be used to compare efficiency of both pattern in this method.