HDR and WCG Image Quality Assessment Using Color Difference Metrics

High dynamic range (HDR) and wide color gamut (WCG) imagery is now mainstream across content creation. Thus, having a reliable way of evaluating HDR systems is essential. One common way of measuring the quality of an HDR system is measuring the color errors introduced along the imaging pipeline. Unfortunately, development of color difference metrics has been based on test patches, as opposed to natural imagery, with evaluation mostly limited to standard dynamic range (SDR) databases. In this paper, we evaluate several color difference metrics on five publicly available HDR distortion databases consisting of natural images and subjective scores. Distortion types include lower frequency distortions such as those from tone mapping as well as higher-frequency distortions resulting from compression artifacts by the various compression schemes such as Joint Photographic Experts Group (JPEG). We analyze these databases with the well-established CIE
$\text{L}^\star \text{a}^\star \text{b}^\star $
metrics (
$\Delta E_{00}, \Delta E_{94}$
) as well as two HDR-specific metrics:
$\Delta E_{z} (j_{z}a_{z}b_{z})$
and
$\Delta E_{ITP} (IC_{T}C_{P})$
. To quantify the performance, we use four standard performance evaluation procedures. We observe that
$\Delta E_{ITP}$
outperforms the other color difference metrics on four out of five databases. We also perform statistical analysis, which demonstrates the effectiveness of using
$\Delta E_{ITP}$
to assess the overall image quality of HDR/WCG content. Weaknesses of all metrics for one database suggest that more advanced spatio-chromatic visual models are worth pursuing.