Directional moving averaging interpolation for texture mapping

In texture mapping, several filtering techniques have been proposed which allow prefiltering of a texture. It has been demonstrated that the shape-variant filter kernel has better performance than its shape-invariant counterpart. However, the conventional shape-variant filtering in which the filtering area is warping-based uses the same kernel for high-detail areas as for low-detail areas of the image in texture space. In this paper we propose a hybrid interpolation filtering method for texture mapping which is based on content-based space-variant directional filtering concepts. First, we classify the local image area in the texture space into three types of blocks: constant, oriented, and irregular blocks. Second, for constant and irregular blocks, we use local average filtering and elliptical weighted average (EWA) filtering, respectively. Third, for oriented blocks, we propose a new filtering method called elliptical weighted adaptive directional moving average (EWADMA) filtering. In the experiments, we show that our method may recover the distorted images with better subjective quality. (C) 1996 Academic Press,Inc.