Abstract

We introduce an algorithm to estimate the optimal exposure parameters from the analysis of a single, possibly under- or over-exposed, image. This algorithm relies on a new quantitative measure of exposure quality, based on the average rendering error, that is, the difference be- tween the original irradiance and its reconstructed value after processing and quantization. In order to estimate the exposure quality in the pres- ence of saturated pixels, we fit a log-normal distribution to the brightness data, computed from the unsaturated pixels. Experimental results are presented comparing the estimated vs. “ground truth” optimal exposure parameters under various illumination conditions.