Radially variant contrast measurement in virtual reality headsets using circular concentric ring patterns

Abstract

Image quality on virtual reality (VR) head‐mounted displays (HMDs) is radially variant on each eyepiece from the visual center (optical axis of the HMD) towards the periphery. The virtual image is blurred at the periphery of display field of view (FOV) resulting in contrast and resolution degradation. Conventional measurement methods adopted from flat‐panel display evaluation do not consider the spatially dependent image artifacts by additional optical components such as HMD lenses and thus may not be adequate to assess the VR image quality. We develop a new method using circular concentric ring patterns to measure the radially variant Michelson contrast on multiple VR HMDs. The results show that measured image contrast reduces towards the periphery of display FOV especially at high‐spatial frequencies. In addition, image quality on VR HMDs can be affected by the 3D position of the eye (or the camera) within the eyebox. Specifically, contrast is further degraded if the interpupillary distance (IPD) setting of the HMD does not match that of the user. It also varies with the entrance pupil location of the light‐measuring device. We propose an efficient method for image quality evaluation that can facilitate the regulatory evaluation of VR headsets.

Geometric distortion on video see‐through head‐mounted displays

“…Before mounting the VST HMD (see Figure 2), the LMD was aligned with the central dot with the optical axis of the LMD perpendicular to the 2D test pattern ( φ = θ = 0). After fixing the placement of the LMD, the eye‐point of VST HMD (the right eyepiece) was aligned with the LMD using a concentric ring method 15 with the entrance pupil of the LMD located at 28 mm from the eyepiece 12…”

Open-Source Pattern Creation Tool for Medical Extended Reality Image Quality Assessment

“…In order to approve these devices for medical use, they must be evaluated on many characteristics to ensure safety and effectiveness. One of the most important evaluations is the quality of the device's display, known as image quality, especially for medical applications (Zhao et al, 2023). The image quality evaluation of virtual and augmented reality devices requires the creation of a variety of different test patterns.…”

“…The image quality evaluation of virtual and augmented reality devices requires the creation of a variety of different test patterns. These test patterns consist of many different shapes that must frequently change their location, size, or color in order to adapt to the many headsets in the market (Beams et al, 2020) (Zhao et al, 2023. The Pattern Creation Tool allows for the creation, editing, and sharing of patterns that work in a mixed reality environment.…”