Year: 1997
Type: conference-paper
Abstract: This paper outlines a technique for treating input texture images as probability density estimators from which new textures, with similar appearance and structural properties, can be sampled.In a two-phase process, the input texture is first analyzed by measuring the joint occurrence of texture discrimination features at multiple resolutions.In the second phase, a new texture is synthesized by sampling successive spatial frequency bands from the input texture, conditioned on the similar joint occurrence of features at lower spatial frequencies.Textures synthesized with this method more successfully capture the characteristics of input textures than do previous techniques.
Author: Jeremy S. De Bonet
Institution: Massachusetts Institute of Technology
Language: English
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W2042371054