Image interpolation based on a multi-resolution directional map

This paper describes an interpolation method that takes into account the edge orientation in order to avoid typical interpolation artifacts (jagging, staircase effects...). It is first based on an edge orientation estimation, performed in the wavelet domain. The estimation uses the multi-resolution features of wavelets to give an accurate and non-biased description of the frequency characteristics of the edges, as well as their orientation. The interpolation is then performed, using the edge orientation estimation, to improve a reference interpolation (cubic-spline for instance). This improvement is carried out by filtering the edges with a gaussian kernel along their direction in order to smooth the contour in the direction parallel to the edge, which avoids disturbing variations across them (jagging and staircase effects). This technique also keeps the sharpness of the transition in the direction perpendicular to the contour to avoid blur. Results are presented on both synthetic and real images, showing the visual impact of the presented method on the quality of interpolated images. Comparisons are made with the usual cubic-spline interpolation, and with other edge-directed interpolation techniques to discuss the choices that have been made in our method.