Quantitative Evaluation and Attribute of Overall Brightness in a High Dynamic Range World

Abstract

Brightness is an attribute of visual perception used to describe the intensity of the light entering the eye. Since human perception is not linearly related to light intensity, characterizing brightness is a challenging task. In standard dynamic range (SDR) imagery, brightness is often quantified using the average picture level (APL), which is the average of all pixels’ code values normalized by the maximum allowed signal code value. APL provides a simple and commonly used brightness metric for SDR; however, its validity for high dynamic range (HDR) content has never been assessed. Due to the higher luminance range that HDR supports, HDR content is encoded using a different transfer function than SDR. Thus, a different distribution of pixel code values is to be expected between HDR and SDR content. In this work, we evaluate the efficiency of the APL metric to quantify the brightness of HDR content. We describe, using patches and professionally graded images, pixel distributions where the APL fails to distinguish relative brightness between pairs of images. To overcome APL shortcomings, we propose a brightness metric based on the geometric mean (GM) and variance of an image’s luma code values. We then conduct two subjective experiments to compare the efficiency of APL and our metric. Results show that the proposed metric predicts more accurately the relative brightness between two frames. However, our results also suggest that a simple statistical model, although useful as a general guideline, cannot be considered accurate enough for HDR content. Therefore, we hypothesize that work on a spatial model might provide a still better fit in characterizing brightness in HDR.