Color interpolation solutions drastically influence the quality of the whole image generation pipeline, so they must guarantee the rendering of high quality pictures by 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. We propose a new adaptive algorithm that decides the interpolation technique to apply to each pixel, according to its neighborhood analysis. Edges are effectively interpolated through a directional filtering approach that interpolates the missing colors, selecting the suitable filter depending on edge orientation. Regions close to edges are interpolated through a simpler demosaicing approach. Thus flat regions are identified and low-pass filtered to eliminate some residual noise and to minimize the annoying green imbalance effect. Finally, an effective false color removal algorithm is used as a postprocessing step 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.