An improved image interpolation algorithm

The paper sets forth an improved edge-directed image interpolation algorithm with low time complexity which is the combination of Newton’s method and edge-directed method. It first partitions images into homogeneous areas and edge areas by setting a preset threshold value based on the local structure characteristics, and then specified algorithms are assigned to interpolate each classified areas, respectively. In this way, it achieves the goals of real-time interpolation and good subjective quality. The interpolated images have higher peak signal noise ratios (PSNR) and better visual effects using proposed method than that of using other algorithms referred to in this paper. Experimental results show that proposed method is highly performed in image interpolation.