Abstract
In this paper, we evaluate the quality of reconstruction i.e. relighting from images obtained by a newly developed multispectral reflectance transformation imaging (MS-RTI) system. The captured MS-RTI images are of objects with different translucency and color. We use the most common methods for relighting the objects: polynomial texture mapping (PTM) and hemispherical harmonics (HSH), as well as the recent discrete model decomposition (DMD). The results show that all three models can reconstruct the images of translucent materials, with the reconstruction error varying with translucency but still in the range of what has been reported for other non-translucent materials. DMD relighted images are marginally better for the most transparent objects, while HSH- and PTM- relighted images appear to be better for the opaquer objects. The estimation of the surface normals of highly translucent objects using photometric stereo is not very accurate. Utilizing the peak of the fitted angular reflectance field, the relighting models, especially PTM, can provide more accurate estimation of the surface normals.
Highlights
Reflectance Transformation Imaging (RTI) is a popular tool for the acquisition of object appearance under different directions of the light source [1]
We evaluate the polynomial texture mapping (PTM) [4], hemispherical harmonics (HSH) [5], and the discrete model decomposition (DMD) [6] regarding their performance on relighting the translucent samples and estimating the surface normals
This offset has lower impact on the structure captured by the SSIM metric (Table 2) which results in the DMD performing similar to PTM and HSH
Summary
Reflectance Transformation Imaging (RTI) is a popular tool for the acquisition of object appearance under different directions of the light source [1]. The acquired images for each of the different light directions are used to model the per-pixel angular reflectance field i.e. the reflectance as a function of the incident light’s angle Other surface properties such as the albedo map or the surface normals of the object can be obtained from an RTI image set. Using an RTI image set, a six-coefficients polynomial function is fitted to the normalized luminance intensities at each pixel, which represents the estimated angular reflectance field This function can be used to visualize, or relight, the object under a light from an arbitrary direction. In the context of this paper, we mention the Hemispherical Harmonics (HSH) [5] and the Discrete Modal Decomposition (DMD) [6] Both HSH and DMD use more complex basis functions than polynomials, and they have improved the relighting over PTM especially for surface points that contain higher frequencies in the angular reflectance field (such as specular highlights) [6]
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