Accurate measurement of images produced by electronic displays is critical for the evaluation of both traditional and computational displays. Traditional display measurement methods based on sparse radiometric sampling and fitting a model are inadequate for capturing spatially varying display artifacts, as they fail to capture high-frequency and pixel-level distortions. While cameras offer sufficient spatial resolution, they introduce optical, sampling, and photometric distortions. Furthermore, the physical measurement must be combined with a model of a visual system to assess whether the distortions are going to be visible. To enable perceptual assessment of displays, we propose a combination of a camera-based reconstruction pipeline with a visual difference predictor, which account for both the inaccuracy of camera measurements and visual difference prediction. The reconstruction pipeline combines HDR image stacking, MTF inversion, vignetting correction, geometric undistortion, homography transformation, and color correction, enabling cameras to function as precise display measurement instruments. By incorporating a Visual Difference Predictor (VDP), our system models the visibility of various stimuli under different viewing conditions for the human visual system. We validate the proposed CameraVDP framework through three applications: defective pixel detection, color fringing awareness, and display non-uniformity evaluation. Our uncertainty analysis framework enables the estimation of the theoretical upper bound for defect pixel detection performance and provides confidence intervals for VDP quality scores. Our code is available on https://github.com/gfxdisp/CameraVDP.

The perception of flicker has been a prominent concern in illumination and electronic display fields for over a century. Traditional approaches often rely on Critical Flicker Frequency (CFF), primarily suited for high-contrast (full-on, full-off) flicker. To tackle varying contrast flicker, the International Committee for Display Metrology (ICDM) introduced a Temporal Contrast Sensitivity Function TCSF$_{IDMS}$ within the Information Display Measurements Standard (IDMS). Nevertheless, this standard overlooks crucial parameters: luminance, eccentricity, and area. Existing models incorporating these parameters are inadequate for flicker detection, especially at low spatial frequencies. To address these limitations, we extend the TCSF$_{IDMS}$ and combine it with a new spatial probability summation model to incorporate the effects of luminance, eccentricity, and area (elaTCSF). We train the elaTCSF on various flicker detection datasets and establish the first variable refresh rate flicker detection dataset for further verification. Additionally, we contribute to resolving a longstanding debate on whether the flicker is more visible in peripheral vision. We demonstrate how elaTCSF can be used to predict flicker due to low-persistence in VR headsets, identify flicker-free VRR operational ranges, and determine flicker sensitivity in lighting design.

The same physical scene seen in bright sunlight and in dusky conditions does not appear identical to the human eye. Similarly, images shown on an 8000 cd/m 2 high-dynamic-range (HDR) display and in a 50 cd/m 2 peak luminance cinema screen also differ significantly in their appearance. We propose a luminance retargeting method that alters the perceived contrast and colors of an image to match the appearance under different luminance levels. The method relies on psychophysical models of matching contrast, models of rod-contribution to vision, and our own measurements. The retargeting involves finding an optimal tone-curve, spatial contrast processing, and modeling of hue and saturation shifts. This lets us reliably simulate night vision in bright conditions, or compensate for a bright image shown on a darker display so that it reveals details and colors that would otherwise be invisible.

The human visual system (HVS) is robust to changes in viewing conditions, such as variations in illumination and viewing distance. Not all elements of our perception stay constant, for example the way we perceive brightness is highly dependent on the background luminance and threshold contrast strongly depends on signal frequency. However, suprathreshold contrast is considered to be constant across viewing conditions and stimuli, the property known as contrast constancy. We intend to verify whether this holds true for a wide range of luminance levels. Results of such measurements could be used to better reproduce images on displays of varying brightness.

Abstract Eleven tone‐mapping operators intended for video processing are analyzed and evaluated with camera‐captured and computer‐generated high‐dynamic‐range content. After optimizing the parameters of the operators in a formal experiment, we inspect and rate the artifacts (flickering, ghosting, temporal color consistency) and color rendition problems (brightness, contrast and color saturation) they produce. This allows us to identify major problems and challenges that video tone‐mapping needs to address. Then, we compare the tone‐mapping results in a pair‐wise comparison experiment to identify the operators that, on average, can be expected to perform better than the others and to assess the magnitude of differences between the best performing operators.