In this paper, texton substitution is implemented by graphics hardware to achieve super resolution of a video stream in realtime processing. The texton substitution method was proposed previously and evaluated for the super resolution of still images, and the textons were defined in wavelet space. In this paper, the wavelet transformation was accelerated by the graphics hardware [Hopf et al. 2001]], followed by two-dimensional filtering of three layers to produce a 10-dimensional vector of the texture at each pixel. The obtained textons were classified into a cluster based on the tree-based clustering technique by the graphics hardware using the pixel shader. This system was applied to the video stream of a face, and the experimental results show the effectiveness of the proposed system.