This study aims at developing an image quality metric for exposure quality, with a transform to just noticeable differences (JNDs) of quality in pictorial scenes. Such a perceptually calibrated exposure metric would allow the prediction of overall image quality by combining exposure with other image attributes. Eight pictorial images were used in the study, and twenty-one observers participated in the subjective evaluation using a softcopy quality ruler method defined in ISO 20462 Part 3. The image simulation path involved seven levels of exposure manipulation, together with two variations in tone mapping algorithms (a global tone mapping algorithm and a local tone mapping algorithm). For each pictorial scene a second image was captured with an exposure target in the scene, allowing the measurement of the scene exposure level. The results showed that an objective metric based on the green channel intensity of the exposure target could be used to predict the optimal exposure level and the quality falloff due to exposure error.