Two-dimensional direction-based interpolation with local centered moments

Interpolation is generally needed to visualize medical images from a limite d number of sliced tomographic images such as CT. In this paper, a novel gr ay-scale image interpolation method, for interpolating two-dimensional imag es accurately and efficiently, called direction-based interpolation, is inv estigated. In this method, the digital image is considered a sampling of th e underlying continuous function, which is also called the image field. If the image is interpolated along the isovalue curves in the image field, ins tead of along the coordinate axes, both the edges and the internal structur es of the objects in the image are well preserved. Initially, the isovalue direction at each point is calculated from the local centered moments of th e image. A specific type of image, called the direction image, is composed from the isovalue directions. Then, the direction image is interpolated int o a high-resolution direction image. The isovalue curve through any point i n the image field is determined from the high-resolution direction image us ing a path-finding technique. A high-resolution gray-scale image with satis factory object structure is then generated by interpolating the original im age linearly along the isovalue curves. Experiments on a set of CT images s how that this method not only preserves the shapes of complicated structure s but also has an efficient computation. The comparison between the digital ly reconstructed radiographs generated from the interpolated result using t he direction-based interpolation method, the traditional linear interpolati on method, and the traditional cubic spline interpolation method shows the promise of the proposed method in radiation treatment planning. (C) 1999 Ac ademic Press.