A model of visual adaptation for realistic image synthesis

Abstract

In this paper we develop a computational model of visual adaptation for realistic image synthesis based on psychophysical experiments. The model captures the changes in threshold visibility, color appearance, visual acuity, and sensitivity over time that are caused by the visual system's adaptation mechanisms. We use the model to display the results of global illumination simulations illuminated at intensities ranging from daylight down to starlight. The resulting images better capture the visual characteristics of scenes viewed over a wide range of illumination levels. Because the model is based on psychophysical data it can be used to predict the visibility and appearance of scene features. This allows the model to be used as the basis of perceptually-based error metrics for limiting the precision of global illumination computations.

Evaluation of Tone Mapping Operators for HDR Video

“…For these four operators we run a parameter adjustment experiment. Processing Intent Description Visual adaptation TMO [FPSG96] Global VSS Use of data from psychophysical experiments to simulate adaptation over time, and effects such as color appearance and visual acuity. Visual response model is based on measurements of threshold visibility as in [War94].…”

Parametric logarithmic type image processing for contrast based auto-focus in extreme lighting conditions

“…First, there is a general acceptance that the human eye never saturates (Ferwerda et al, 1996). The lack of saturation is valid also for any closed mathematical model.…”

Evaluation of HDR video tone mapping for mobile devices

“…Global operators are simple and fast and they preserve the global contrast of the image, but are unable to maintain the local contrast of the image which can result in a loss of details in some regions. In this category of TMOs we have, for instance, the Model of Visual Adaptation TMO [4], the Brightness Reproduction TMO [10], Quantization Techniques TMO [11] and the Histogram Adjustment TMO [12].…”

“…In this paper we present the results of the evaluation of six HDR video TMOs that focus on different properties. The TMOs evaluated were: Spatio-Temporal based on a Retina model [3], the model of visual adaptation [4], the method proposed by [5] that encodes HDR video using a model of human cones, the display adaptive technique [6], a time-dependent visual adaptation approach [7], and the TMO proposed by Boitard et al [8] that takes account temporal coherency. This evaluation intends to determine:…”