Calibrated image appearance reproduction

Abstract

Managing the appearance of images across different display environments is a difficult problem, exacerbated by the proliferation of high dynamic range imaging technologies. Tone reproduction is often limited to luminance adjustment and is rarely calibrated against psychophysical data, while color appearance modeling addresses color reproduction in a calibrated manner, albeit over a limited luminance range. Only a few image appearance models bridge the gap, borrowing ideas from both areas. Our take on scene reproduction reduces computational complexity with respect to the state-of-the-art, and adds a spatially varying model of lightness perception. The predictive capabilities of the model are validated against all psychophysical data known to us, and visual comparisons show accurate and robust reproduction for challenging high dynamic range scenes.

Efficient, high brightness, high dynamic range projection

“…bright for outdoor displays, dim for cinema) [Reinhard et al 2012]. HDR is then defined as a large range of displayable luminance values above and below this adaptation level, typically several orders of magnitude wide.…”

The high dynamic range imaging pipeline : Tone-mapping, distribution, and single-exposure reconstruction

“…Another approach is to aim at minimizing the changes in contrasts, given that the dynamic range is compressed to a certain display device [77,170]. Other SRP goals include, for example, preservation of visibility [264], perceived lightness [133], color appearance [138,212], and temporal consistency [38,107].…”

“…For example, there are examples of methods that perform the compression in the gradient [89,148,254] or contrast [167] domain. Also, a number of methods attempt to model the appearance of colors [6,86,129,138,198,212]. However, the most common method is to only consider luminance, and restore colors after this has been compressed [220].…”

High-Pressure Mercury Gas-Discharge Lamp

“…In contrast to the operators discussed so far, CAMs process each channel of the image separately rather than only compress luminance [26]. Typically, such models employ both a forward and an inverse step, taking the scene and viewing parameters into account, although it was recently shown that the inverse step may be bypassed, while still accurately reproducing color appearance [27]. …”