Adaptive color demosaicing and false color removal

Color interpolation solutions drastically influence the quality of the whole image generation pipeline, so they must guarantee the rendering of high quality pictures avoiding typical artifacts such as blurring, zipper effects and false colors. Moreover, demosaicing should avoid emphasizing typical artifacts of real sensors data, such as noise and green imbalance effect, which would be further accentuated by the subsequent steps of the processing pipeline. In this paper we propose a new adaptive algorithm, which decides the interpolation technique to apply to each pixel, according to its neighborhood analysis. Edges are effectively interpolated through a directional filtering approach which interpolates the missing colors selecting the suitable filter depending on the edge orientation. Regions close to edges are interpolated through a simpler demosaicing approach. Thus flat regions are identified low pass filtered in order to eliminate some residual noise and to minimize the annoying green imbalance effect. Finally an effective false colors removal algorithm is used as a post-processing step, in order to eliminate residual color errors. The experimental results show how sharp edges are preserved whereas undesired zipper effects are reduced, improving the edge resolution itself and obtaining superior image quality.