Super Resolution Method Using Texton Substitution

Abstract

The resolution of a texture image in computer graphics is determined by the camera system used to take the image. Zooming in on the object beyond the optical resolution results in a loss of edges and details. We developed a “super resolution” method that uses a database of textures and texton substitution to create plausible high-frequency detail in enlarged texture images. Conventional example-based super-resolution techniques involve a high computational cost and users must provide the optimal parameters for the input image. Using texton in the wavelet space and a pixel-based (not a patch-based) substitution reduces the computational cost.