Interlaced to progressive scan conversion Using fuzzy edge-based line average algorithm

De-interlacing methods realize the interlaced to progressive conversion required in many applications. Among them, intra-field methods are widely used for their good trade off between performance and computational cost. In particular, the ELA algorithm is well-known for its advantages in reconstructing the edges of the images, although it degrades the image quality where the edges are not clear. The algorithm proposed in this paper uses a simple fuzzy system which models heuristic rules to improve the KLA rules. It can be implemented easily in software and hardware since the increase in computational cost is very low. Simulation results are included to illustrate the advantages of the proposed fuzzy ELA algorithm in de-interlacing non noisy and noisy images.