Vision researchers have proposed many phenomena and mechanisms relating to surface perception (Gibson,
1950; Kanizsa, Legrenzi, & Bozzi,
1979; Komatsu,
2006; Nakayama & Shimojo, 1991; Paradiso & Nakayama,
1992). In particular, perceptual transparency has fascinated many researchers for decades (Adelson & Anandan,
1990; Anderson,
1997; Beck & Ivry,
1988; Metelli,
1974). Perceptual transparency has two main components. One is surface formation, through which the visual system determines foreground and background layers. The other is color scission (Gerbino, Stultiens, Troost, & de Weert,
1990; Khang & Zaidi,
2002), wherein the visual system decomposes a single color input into foreground and background colors. In conventional transparency effects the two components are hard to separate, as they are like two sides of the same coin because they are based on tightly connected image information. Surface-layer formation is based on the spatiotemporal properties of surface boundary contours, such as x-junctions (Adelson & Anandan,
1990; Anderson,
1997; Beck & Ivry,
1988), occluding motion (Cicerone, Hoffman, Gowdy, & Kim,
1995; Miyahara & Cicerone,
1997), and binocular disparity (Kingdom, Blakeslee, & McCourt,
1997; Tse,
2005); while color scission is based on the image changes (e.g., luminance or color contrast) across the surface boundary contours (Adelson,
1993,
2000; Shevell & Kingdom,
2008). In conventional perceptual transparency effects, the simulated transparent materials are not perfectly transparent. They are visible due to such optical factors as partial light absorption and scattering within the layer, and weak light reflectance at the surface. In natural image formation, these factors produce visible image changes in luminance, color, or blurring at the outer boundary of a transparent layer. These image changes provide cues for the visual system to infer the presence and properties of transparent layers that are then converted into what is actually perceived.