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A Novel Framework for Highlight Reflectance Transformation Imaging

Andrea Giachetti, Irina Ciortan, Claudia Daffara, Giacomo Marchioro, Ruggero Pintus, and Enrico Gobbetti

2017

Abstract

We propose a novel pipeline and related software tools for processing the multi-light image collections (MLICs) acquired in different application contexts to obtain shape and appearance information of captured surfaces, as well as to derive compact relightable representations of them. Our pipeline extends the popular Highlight Reflectance Transformation Imaging (H-RTI) framework, which is widely used in the Cultural Heritage domain. We support, in particular, perspective camera modeling, per-pixel interpolated light direction estimation, as well as light normalization correcting vignetting and uneven non-directional illumination. Furthermore, we propose two novel easy-to-use software tools to simplify all processing steps. The tools, in addition to support easy processing and encoding of pixel data, implement a variety of visualizations, as well as multiple reflectance-model-fitting options. Experimental tests on synthetic and real-world MLICs demonstrate the usefulness of the novel algorithmic framework and the potential benefits of the proposed tools for end-user applications.

Reference and download information

Andrea Giachetti, Irina Ciortan, Claudia Daffara, Giacomo Marchioro, Ruggero Pintus, and Enrico Gobbetti. A Novel Framework for Highlight Reflectance Transformation Imaging. Computer Vision and Image Understanding, 2017. https://doi.org/10.1016/j.cviu.2017.05.014. To appear.

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Bibtex citation record

@Article{Giachetti:2017:NFH,
    author = {Andrea Giachetti and Irina Ciortan and Claudia Daffara and Giacomo Marchioro and Ruggero Pintus and Enrico Gobbetti},
    title = {A Novel Framework for Highlight Reflectance Transformation Imaging},
    journal = {Computer Vision and Image Understanding},
    year = {2017},
    abstract = { We propose a novel pipeline and related software tools for processing the multi-light image collections (MLICs) acquired in different application contexts to obtain shape and appearance information of captured surfaces, as well as to derive compact relightable representations of them. Our pipeline extends the popular Highlight Reflectance Transformation Imaging (H-RTI) framework, which is widely used in the Cultural Heritage domain. We support, in particular, perspective camera modeling, per-pixel interpolated light direction estimation, as well as light normalization correcting vignetting and uneven non-directional illumination. Furthermore, we propose two novel easy-to-use software tools to simplify all processing steps. The tools, in addition to support easy processing and encoding of pixel data, implement a variety of visualizations, as well as multiple reflectance-model-fitting options. Experimental tests on synthetic and real-world MLICs demonstrate the usefulness of the novel algorithmic framework and the potential benefits of the proposed tools for end-user applications. },
    note = {To appear},
    url = {http://vic.crs4.it/vic/cgi-bin/bib-page.cgi?id='Giachetti:2017:NFH'},
}