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    Feature-aware natural texture synthesis

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    Type
    Article
    Authors
    Wu, Fuzhang
    Dong, Weiming
    Kong, Yan
    Mei, Xing
    Yan, Dongming cc
    Zhang, Xiaopeng
    Paul, Jean Claude
    KAUST Department
    Visual Computing Center (VCC)
    Date
    2014-12-04
    Online Publication Date
    2014-12-04
    Print Publication Date
    2016-01
    Permanent link to this record
    http://hdl.handle.net/10754/566111
    
    Metadata
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    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.
    Publisher
    Springer Nature
    Journal
    The Visual Computer
    DOI
    10.1007/s00371-014-1054-y
    ae974a485f413a2113503eed53cd6c53
    10.1007/s00371-014-1054-y
    Scopus Count
    Collections
    Articles; Visual Computing Center (VCC)

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