Direction-Oriented Line Interpolation Using Geometric Duality
Sangjun Park, Gwanggil Jeon, Jechang Jeong · 2010
In this paper, a direction-oriented covariance based deinterlacing method is presented. First, the local direction of edge is determined by modified edge-based line average (MELA) method. Then, based on the geometric duality, the optimal interpolation coefficients for the neighbor pixels of corresponding direction are estimated using the Wiener filtering. Experimental results prove that the proposed method provides a significant improvement over the other existing deinterlacing methods.