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Energy-adaptive color selection or design has recently received much attention with the spreading of the organic light emitting diode (OLED) display. Current solutions optimize color sets by analyzing the energy consumption of the 2D rendered images with the screen-space energy model. The comprehensive influence with respect to the volume visualization like the illumination model, the light, as well as the semi-transparency is not considered. This paper presents an energy-saving color scheme selection and optimization approach for direct volume rendering on OLED displays. We propose an illumination-aware energy estimating model that formulates a simplified equation between the display energy consumption and a specific color scheme in object space, making it practical to achieve global color scheme optimization. By performing the color scheme optimization, we obtain an optimal color transfer function, with which we can generate energy-aware direct volume rendering images for OLED display. Experimental results demonstrate the efficiency of our approach on OLED display systems. [ABSTRACT FROM AUTHOR]

Abstract: Current energy-saving color design approaches can be classified into two categories, namely, context-aware dimming and color remapping. The former darkens individual regions with respect to the user interactions, and the latter replaces the color set with a new color set that yields lower energy consumption. Both schemes have drawbacks: color dimming tends to cause loss of perceptual quality, and color remapping is an offline color design process. This paper introduces a novel saliency-guided color dimming scheme for OLED displays in both the context of 3D visualization and 2D visualization. The key idea is to eliminate undesired details while enhancing the visually salient features of each frame on-the-fly by leveraging the color and spatial information. A parallelizable image-space salient region detection algorithm is introduced to make the entire process GPU-friendly and real-time. We apply our approach on several representative visualization scenarios and conduct a preliminary user study. Experimental results demonstrate the effectiveness, efficiency, and quality of our approach. [Copyright &y& Elsevier]

Abstract: Fast rendering of dynamic scenes with natural illumination, all-frequency shadows and spatially varying reflections is important but challenging. One main difficulty brought by moving objects is that the runtime visibility update of dynamic occlusion is usually time-consuming and slow. In this paper, we present a new visibility sampling technique and show that efficient all-frequency rendering of dynamic scenes can be achieved by sampling visibility of dynamic objects in an adaptive and parallel way. First, we propose a two-level adaptive sampling scheme to distribute sample points spatially and compute visibility maps angularly on each sample point. Then, we present a parallel hemispherical distance transform to convert these visibility maps into spherical signed distance fields. Finally, using such a distance-based visibility representation, we integrate our visibility sampling algorithm in the all-frequency rendering framework for scenes with spatially varying BRDFs. With an entire GPU-based implementation, our algorithm enables interactive all-frequency rendering of moderate dynamic scenes with environment lighting and spatially varying reflectance. [Copyright &y& Elsevier]