Matching visual induction effects on screens of different size

In the film industry, the same movie is expected to be watched on displays of vastly different sizes, from cinema screens to mobile phones. But visual induction, the perceptual phenomenon by which the appearance of a scene region is affected by its surroundings, will be different for the same image shown on two displays of different dimensions. This phenomenon presents a practical challenge for the preservation of the artistic intentions of filmmakers, because it can lead to shifts in image appearance between viewing destinations. In this work, we show that a neural field model based on the efficient representation principle is able to predict induction effects and how, by regularizing its associated energy functional, the model is still able to represent induction but is now invertible. From this finding, we propose a method to preprocess an image in a screen-size dependent way so that its perception, in terms of visual induction, may remain constant across displays of different size. The potential of the method is demonstrated through psychophysical experiments on synthetic images and qualitative examples on natural images

Gamut extension for cinema

Emerging display technologies are able to produce images with a much wider color gamut than those of conventional distribution gamuts for cinema and TV, creating an opportunity for the development of gamut extension algorithms (GEAs) that exploit the full color potential of these new systems. In this paper, we present a novel GEA, implemented as a PDE-based optimization procedure related to visual perception models, that performs gamut extension (GE) by taking into account the analysis of distortions in hue, chroma, and saturation. User studies performed using a digital cinema projector under cinematic (low ambient light, large screen) conditions show that the proposed algorithm outperforms the state of the art, producing gamut extended images that are perceptually more faithful to the wide-gamut ground truth, as well as free of color artifacts and hue shifts. We also show how currently available image quality metrics, when applied to the GE problem, provide results that do not correlate with users' choices

Gamut extension for cinema: psychophysical evaluation of the state of the art and a new algorithm

Wide gamut digital display technology, in order to show its full potential in terms of colors, is creating an opportunity to develop gamut extension algorithms (GEAs). To this end, in this work we present two contributions. First we report a psychophysical evaluation of GEAs specifically for cinema using a digital cinema projector under cinematic (low ambient light) conditions; to the best of our knowledge this is the first evaluation of this kind reported in the literature. Second, we propose a new GEA by introducing simple but key modifications to the algorithm of Zamir et al. This new algorithm performs well in terms of skin tones and memory colors, with results that look natural and which are free from artifacts. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.This work was supported by the European Research Council, Starting Grant ref. 306337, by Spanish grant ref. TIN2012-38112 and by ICREA Academi

Gamut extension for cinema: psychophysical evaluation of the state of the art and a new algorithm

Wide gamut digital display technology, in order to show its full potential in terms of colors, is creating an opportunity to develop gamut extension algorithms (GEAs). To this end, in this work we present two contributions. First we report a psychophysical evaluation of GEAs specifically for cinema using a digital cinema projector under cinematic (low ambient light) conditions; to the best of our knowledge this is the first evaluation of this kind reported in the literature. Second, we propose a new GEA by introducing simple but key modifications to the algorithm of Zamir et al. This new algorithm performs well in terms of skin tones and memory colors, with results that look natural and which are free from artifacts. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.This work was supported by the European Research Council, Starting Grant ref. 306337, by Spanish grant ref. TIN2012-38112 and by ICREA Academi