Predicting visible differences in high dynamic range images: model and its calibration

New imaging and rendering systems commonly use physically accurate lighting information in the form of highdynamic range (HDR) images and video. HDR images contain actual colorimetric or physical values, which can span 14 orders of magnitude, instead of 8-bit renderings, found in standard images. The additional precision and quality retained in HDR visual data is necessary to display images on advanced HDR display devices, capable of showing contrast of 50,000:1, as compared to the contrast of 700:1 for LCD displays. With the development of high-dynamic range visual techniques comes a need for an automatic visual quality assessment of the resulting images. In this paper we propose several modifications to the Visual Difference Predicator (VDP). The modifications improve the prediction of perceivable differences in the full visible range of luminance and under the adaptation conditions corresponding to real scene observation. The proposed metric takes into account the aspects of high contrast vision, like scattering of the light in the optics (OTF), nonlinear response to light for the full range of luminance, and local adaptation. To calibrate our HDR VDP we perform experiments using an advanced HDR display, capable of displaying the range of luminance that is close to that found in real scenes.