This article presents a new algorithm for spatial deinterlacing that could easily be integrated in a more complete deinterlacing system, typically a spatio-temporal motion adaptive one. The spatial interpolation part often fails to reconstruct close to horizontal lines with a proper continuity, leading to highly visible artifacts. Our system preserves the structure continuity taking into account that the misinterpolated points usually correspond to local value extrema. The processing is based on chained lists and connected graph construction. The new interpolation method is restricted to such structures, for the rest of the image, a proper traditional directional spatial interpolation gives satisfactory results already. Although the number of pixels affected by the extrema interpolation is relatively small, the overall image quality is subjectively well improved. Moreover, our solution allows to gain back one of the major advantages of motion compensation methods, without having to afford their complexity cost.

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This article presents a new algorithm for spatial deinterlacing that could easily be integrated in a more complete deinterlacing system. The spatial interpolation process often fails to reconstruct edges that are diagonal or close to horizontal, leading to highly visible artifacts. Our solution aims at preserving the linear structure continuity. It connects pieces of horizontal edges coming from neighboring lines to build graphs which are then simplified in branches that represent the linear structure of the scene. These branches give the exact direction in which the interpolation has to be done. For the rest of the image, a traditional directional spatial interpolation gives satisfactory results already. Although the number of pixels interpolated with this method is relatively small, the overall image quality is subjectively well improved.

No abstract