A local model of eye adaptation for high dynamic range images

In the real world, the human eye is confronted with a wide range of luminances from bright sunshine to low night light. Our eyes cope with this vast range of intensities by adaptation; changing their sensitivity to be responsive at di erent illumination levels. This adaptation is highly localized, allowing us to see both dark and bright regions of a high dynamic range environment. In this paper we present a new model of eye adaptation based on physiological data. The model, which can be easily integrated into existing renderers, can function either as a static local tone mapping operator for single high dynamic range image, or as a temporal adaptation model taking into account time elapsed and intensity of preadaptation for a dynamic sequence. We nally validate our technique with a high dynamic range display and a psychophysical study.(undefined

Fully-automatic inverse tone mapping algorithm based on dynamic mid-level tone mapping

High Dynamic Range (HDR) displays can show images with higher color contrast levels and peak luminosities than the common Low Dynamic Range (LDR) displays. However, most existing video content is recorded and/or graded in LDR format. To show LDR content on HDR displays, it needs to be up-scaled using a so-called inverse tone mapping algorithm. Several techniques for inverse tone mapping have been proposed in the last years, going from simple approaches based on global and local operators to more advanced algorithms such as neural networks. Some of the drawbacks of existing techniques for inverse tone mapping are the need for human intervention, the high computation time for more advanced algorithms, limited low peak brightness, and the lack of the preservation of the artistic intentions. In this paper, we propose a fully-automatic inverse tone mapping operator based on mid-level mapping capable of real-time video processing. Our proposed algorithm allows expanding LDR images into HDR images with peak brightness over 1000 nits, preserving the artistic intentions inherent to the HDR domain. We assessed our results using the full-reference objective quality metrics HDR-VDP-2.2 and DRIM, and carrying out a subjective pair-wise comparison experiment. We compared our results with those obtained with the most recent methods found in the literature. Experimental results demonstrate that our proposed method outperforms the current state-of-the-art of simple inverse tone mapping methods and its performance is similar to other more complex and time-consuming advanced techniques

Apollo experience report: Simulation of manned space flight for crew training

Through space-flight experience and the development of simulators to meet the associated training requirements, several factors have been established as fundamental for providing adequate flight simulators for crew training. The development of flight simulators from Project Mercury through the Apollo 15 mission is described. The functional uses, characteristics, and development problems of the various simulators are discussed for the benefit of future programs

An Investigation of Daylighting Performance in Sidelit Spaces

The positive influence of daylight on people’s work and well-being has been confirmed in many studies. However, excessive daylight causes discomfort glare, which decreases work productivity, impairs occupants’ vision, and may even cause headaches. Substantial studies explored glare by correlating physical lighting measurements and subjective evaluations. With the development of High Dynamic Range (HDR) image techniques, dynamic changes of daylighting distributions can be effectively captured. Consequently, more studies paired HDR image techniques with subject evaluations to explore glare. However, studies merely relying on field measurements are not only time-consuming and labor-intensive but may also disturb occupants. To address these problems, this dissertation proposed the method of integrating three research tools, HDR image techniques, simulations, and questionnaire surveys, to investigate daylight glare. Using sidelit spaces across five buildings as the example, this dissertation aimed to demonstrate the accuracy of simulation results and the correlations between subject occupant evaluations and physical lighting data derived from both field measurements and simulation results. This dissertation is comprised of three sections. The first section focused on field measurements. Over 200 HDR images across five buildings were taken and analyzed using select visual discomfort metrics. The results showed that daylight glare probability (DGP) outperformed the other visual discomfort metrics in terms of identifying intolerable and imperceptible glare. The second section utilized these HDR images to calibrate four of the five buildings’ Radiance models. The relative RMSE of simulated vertical eye illuminance under both the Perez all-weather sky model and the hybrid photo-radiometer sky model were 23.7% and 21.2%, respectively. The frequencies of accurate glare prediction under both sky models were 93.9% and 95.5%, respectively. The results indicated that Radiance models with precise geometries and material properties can accurately represent the real lighting environments. Finally, the third section paired questionnaire surveys with both the HDR image technique and simulations to investigate daylight qualities within an open-plan office. The study found that taller windows, proximity to windows, and facing towards windows caused severe glare. By removing workstation partitions and arranging seating orientations perpendicular to the windows, the renovated layout design increased occupant satisfaction with their daylighting environments and tolerance for daylight glare. The last section demonstrated the effectiveness of integrating the three tools in lighting studies and the importance of interior layout and furniture designs in terms of daylight glare reduction

A Model of Local Adaptation

The visual system constantly adapts to different luminance levels when viewing natural scenes. The state of visual adaptation is the key parameter in many visual models. While the time-course of such adaptation is well understood, there is little known about the spatial pooling that drives the adaptation signal. In this work we propose a new empirical model of local adaptation, that predicts how the adaptation signal is integrated in the retina. The model is based on psychophysical measurements on a high dynamic range (HDR) display. We employ a novel approach to model discovery, in which the experimental stimuli are optimized to find the most predictive model. The model can be used to predict the steady state of adaptation, but also conservative estimates of the visibility(detection) thresholds in complex images.We demonstrate the utility of the model in several applications, such as perceptual error bounds for physically based rendering, determining the backlight resolution for HDR displays, measuring the maximum visible dynamic range in natural scenes, simulation of afterimages, and gaze-dependent tone mapping