It can be easily observed that a white support printed with halftone ink layers changes color when coated with a clear layer. The color change can be explained by purely optical phenomena, for example the perception of a different amount of light scattered by the ink-matter interface if the observer is not too far from the specular direction. But color change can be also observed far from the specular direction, especially with halftone colors, where the support has not a homogeneous reflectance at the mesoscopic scale. This is due to subsurface optical phenomena investigated only recently in the case of uniformly colored support. In the present paper, thanks to an original optical model dedicated to halftone colors, we show that this subsurface phenomenon tends to increase the chance for light to meet several ink dots, therefore the chance to be absorbed.

Reflectance Transformation Imaging (RTI) is a computational photographic method that captures an object’s surface shape & color and enables the interactive re-lighting of the subject from any direction. RTI model of an object is built from multiple images of it captured by a stationary camera but varying light directions. By changing the direction of the light, the respective micro-geometry of the object is highlighted. The RTI acquisition process is often long, and tedious when it is not automated. It requires expertise to define for each analysed object which are the number and the relevant lighting positions in the acquisition sequence. In this paper, we present our novel Next Best Light Position (NBLP) method to address this issue. The proposed method is based on the principle of a gradient descent allowing in an adaptive and iterative way, to automatically define the most appropriate lighting directions for the RTI acquisition of an object/surface.

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.

How we visually perceive non-emissive objects in our surrounding depends on the interaction of light with the optical characteristics of the materials that comprise them. The macroscopic surface roughness can also influence the appearance through shadowing and interreflections. In this work, we use a structured light scanner to estimate the surface structure of near-planar surfaces, namely of printing textiles. We compare our scans, both qualitatively and quantitatively, to those from a commercial highgrade profilometer based on the confocal principle. We achieve comparable results to the profilometer on samples with moderately complex surfaces. We discuss the possible reasons for errors in the scans of complex surfaces, thus providing guidelines for robust depth estimation. This comparison can help other researchers build more robust acquisition setups by understanding and minimizing the errors inherent to the reconstruction methods.

Goniospectrophotometer ConDOR designed by CNAM, France, measures BRDF at very high angular resolution (0.014°), comparable to that of human vision. This is achieved using a very collimated light beam and a dedicated Fourier lens. Interestingly, the BRDF of glossy surfaces measured at this resolution exhibits a granular aspect around the specular direction, like a rapid angular fluctuation, which is not detection noise as it is repeatable between successive measurements on the same sample. Based on our experiments using ConDOR as well as numerical simulations, we claim that this granular aspect comes from an optical effect called speckle, which occurs every time a sufficiently coherent light beam — which is inevitably the case when the incident solid angle is very narrow — strikes a rough surface. First elements of confirmation are given in this paper.

Traditionally, the appearance of an object in an image is edited to elicit a preferred perception. However, the editing method might be arbitrary and might not consider the human perception mechanism. In this study, the authors explored image-based leather “authenticity” editing using an estimation model that considers a perception mechanism derived in their previous work. They created leather rendered images by emphasizing or suppressing image properties corresponding to the “authenticity.” Subsequently, they performed two subjective experiments, one using fully edited images and another using partially edited images whose specular reflection intensity was constant. Participants observed the leather rendered images and evaluated the differences in the perception of “authenticity.” The authors found that the “authenticity” perception could be changed by manipulating the intensity of specular reflection and the texture (grain and surface irregularity) in the images. The results of this study could be used to tune the properties of images to make them more appealing.