Antipole Clustering for Fast Texture Synthesis

This paper describes a new method for analysis/synthesis of textures using a non-parametric multi-resolution approach able to reproduce efficiently the generative stochastic process of a wide class of real texture images. This is realized through a new data structure the Antipole Tree and a suitable research strategy able to outperform both the classical linear full-search heuristic and the TSVQ (Tree Structure Vector Quantization) acceleration used in previous related works. Experimental results performed on an exhaustive set of textures [VisTex] show the effectiveness of the proposed approach. Keywords Texture Synthesis, Pyramid Decomposition, Antipole Clustering, Nearest-neighbor.

• Type: Conference
• Year: 2003
• Where: WSCG
• Authors: Sebastiano Battiato, Alfredo Pulvirenti, Diego Reforgiato Recupero
• Keywords: Generative Stochastic Process, Non-parametric Multi-resolution Approach, Structure Vector Quantization, WSCG 2003