Deterministic texture analysis and synthesis using tree structure vector quantization

Texture analysis and synthesis is very important for computer graphics, vision, and image processing. This paper describes an algorithm which can produce new textures with a matching visual appearance from a given example image. Our algorithm is based on a model that characterizes textures using a nonlinear deterministic function. During analysis, an example texture is summarized into this function using tree structure vector quantization. An output texture, initially random noise, is then synthesized from this estimated function. Compared to existing approaches, our algorithm can efficiently generate a wide variety of textures. The effectiveness of our approach is demonstrated using standard test images from the Brodatz texture album.