This paper proposes an adaptive edge-directed interpolation algorithm using multidirectional neighbor pixels. In order to restore multidirectional edges, a missing pixel is estimated as a weighted sum of 12 neighbor pixels. Based on the geometric duality between a low resolution image and a high resolution image, interpolation coefficients are predicted using Wiener filter theory. In order to reduce the computational complexity, interpolation region selection method is also proposed. An edge map for a low resolution image is obtained by canny edge detector. By analyzing edge continuities, only long edge regions are interpolated using 12 neighbor pixels. Short edge regions are interpolated by new edge-directed interpolation, and even regions are interpolated by a linear interpolation. Simulation results show that a proposed method restores major edges with several directions better than other methods in subjective tests while showing fair performance in objective tests.