A Novel Image Interpolation Algorithm Based on Directional Extension of AP-DCT Interpolation Kernel

Abstract

In order to decrease the smoothing effect of traditional linear interpolation methods and avoid the complexity of edge-directed adaptive algorithms, a novel image interpolation algorithm based on the directional extension of linear interpolation kernel is proposed. At first, All Phase Non-subsampled Contourlet Transform is used to divide the image of low resolution into different frequencies and directional sub-band images, and then the All Phase Discrete Cosine Transform Interpolation Kernel is extended to 2-D with distinct directional priorities and used to enlarge respective sub-band images. The interpolated sub-band images are finally synthesized as the upsampled image. Simulation results demonstrate that the proposed algorithm improves both the subjective and objective quality of the interpolated images over conventional linear interpolation. The computation complexity of the proposed algorithm is moderate and it can be implemented with parallel structure so as to save more computation time.