Iterative Image Interpolation vs. Traditional Interpolation Methods

Image interpolation is an important image processing operation applied in diverse areas ranging from computer graphics, rendering, editing, medical image reconstruction, and online image viewing. In this paper, image is interpolated from a lower resolution (LR) to a higher resolution (HR) based on the combination of two different procedures. First, an adaptive algorithm interpolating locally image pixel values along the direction is applied, where second order image derivative is low. Then interpolated values are modified using an iterative refinement to minimize the differences in second order image derivatives, maximize the second order derivative values and smooth the curves. The first algorithm itself provides edge-preserving images that are measurable better than those obtained with conventional methods presented in this literature. Objective and subjective tests on a series of natural images show the advantages of the used technique over existing approaches.