Feature-aware natural texture synthesis

Fuzhang Wu, Weiming Dong, Yan Kong, Xing Mei, Dongming Yan, Xiaopeng Zhang, Jean Claude Paul

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

This article presents a framework for natural texture synthesis and processing. This framework is motivated by the observation that given examples captured in natural scene, texture synthesis addresses a critical problem, namely, that synthesis quality can be affected adversely if the texture elements in an example display spatially varied patterns, such as perspective distortion, the composition of different sub-textures, and variations in global color pattern as a result of complex illumination. This issue is common in natural textures and is a fundamental challenge for previously developed methods. Thus, we address it from a feature point of view and propose a feature-aware approach to synthesize natural textures. The synthesis process is guided by a feature map that represents the visual characteristics of the input texture. Moreover, we present a novel adaptive initialization algorithm that can effectively avoid the repeat and verbatim copying artifacts. Our approach improves texture synthesis in many images that cannot be handled effectively with traditional technologies.
Original languageEnglish (US)
Pages (from-to)43-55
Number of pages13
JournalThe Visual Computer
Volume32
Issue number1
DOIs
StatePublished - Dec 4 2014

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Software
  • Computer Vision and Pattern Recognition

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