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In recent years, improvements in display image quality have made it easier to perceive rich object information, such as gloss and transparency, from images, known as shitsukan. Do the different display specifications in the world affect their appearance? Clarifying the effects of differences in pixel structure on shitsukan perception is necessary to realize shitsukan management for displays with different hardware structures, which has not been fully clarified before. In this study, we experimentally investigated the effects of display pixel arrays on the perception of glossiness and transparency. In a visual evaluation experiment, we investigated the effects of three types of sub-pixel arrays (RGB, RGBW, and PenTile) on the perception of glossiness and transparency using natural images. The results confirmed that sub-pixel arrays affect the appearance of glossiness and transparency. A general relationship of RGB > PenTile > RGBW for glossiness and RGB > RGBW > PenTile for transparency was found; however, detailed analysis, such as cluster analysis, confirmed that the relative superiority of these sub-pixel arrays may vary depending on the observer and image content. [ABSTRACT FROM AUTHOR]

In recent years, improvements in display image quality have made it easier to perceive rich object information, such as gloss and transparency, from images, known as shitsukan. Do the different display specifications in the world affect their appearance? Clarifying the effects of differences in pixel structure on shitsukan perception is necessary to realize shitsukan management for displays with different hardware structures, which has not been fully clarified before. In this study, we experimentally investigated the effects of display pixel arrays on the perception of glossiness and transparency. In a visual evaluation experiment, we investigated the effects of three types of sub-pixel arrays (RGB, RGBW, and PenTile) on the perception of glossiness and transparency using natural images. The results confirmed that sub-pixel arrays affect the appearance of glossiness and transparency. A general relationship of RGB > PenTile > RGBW for glossiness and RGB > RGBW > PenTile for transparency was found; however, detailed analysis, such as cluster analysis, confirmed that the relative superiority of these sub-pixel arrays may vary depending on the observer and image content.

Shitsukan is a comprehensive concept for both an object’s material （e.g., metal, wood） and its properties （e.g., roughness, glossiness） based on either visual, auditory, or tactile information. Shitsukan plays an important role within human activity. Recently, shitsukan perception, or material perception, is assumed to be based on statistical inferencing from multisensory information and several studies have investigated the neural basis of such statistical inferencing. In this paper, we discuss the mechanisms of material perception in terms of multisensory integration research and propose a new perspective from which to elucidate the information processing underlying shitsukan. [ABSTRACT FROM AUTHOR]

We often estimate, or perceive, the quality of materials, surfaces, and objects, what the Japanese refer to as 'shitsukan', by means of several of our senses. The majority of the literature on shitsukan perception has, though, tended to focus on the unimodal visual evaluation of stimulus properties. In part, this presumably reflects the widespread hegemony of the visual in the modern era and, in part, is a result of the growing interest, not to mention the impressive advances, in digital rendering amongst the computer graphics community. Nevertheless, regardless of such an oculocentric bias in so much of the empirical literature, it is important to note that several other senses often do contribute to the impression of the material quality of surfaces, materials, and objects as experienced in the real world, rather than just in virtual reality. Understanding the multisensory contributions to the perception of material quality, especially when combined with computational and neural data, is likely to have implications for a number of fields of basic research as well as being applicable to emerging domains such as, for example, multisensory augmented retail, not to mention multisensory packaging design. [ABSTRACT FROM AUTHOR]