New image interpolation method based on sub-regional and multi-directional data fusion

To solve the contradictory of speed and accuracy of the existing interpolation method, an interpolation method based on sub-regional and multi-directional data fusion is presented. The new method divides images into flat areas and edge-regions. The bilinear algorithm is used in flat areas, and the improved algorithm is used in edge-regions. Based on the inverse ratio of the distance square, the improved algorithm fully considers four-direction estimated results of the nearest horizontal, vertical and two diagonal directions using 12 pixels selected from 4×4 neighborhood. A final interpolation result is obtained by calculating weights of vertical distance and direction gradient. The experimental result shows that the proposed interpolation method costs less time and can make edges of image more natural and clear. Moreover, it can be applied to any multiples of interpolation amplification.