With the development of image-based applications, assessing the quality of images has become increasingly important. Although our perception of image quality changes as we age, most existing image quality assessment (IQA) metrics make simplifying assumptions about the age of observers, thus limiting their use for age-specific applications. In this work, we propose a personalized IQA metric to assess the perceived image quality of observers from different age groups. Firstly, we apply an age simulation algorithm to compute how an observer with a particular age would perceive a given image. More specifically, we process the input image according to an age-specific contrast sensitivity function (CSF), which predicts the reduction of contrast visibility associated with the aging eye. We combine age simulation with existing IQA metrics to calculate the age-specific perceived image quality score. To validate the effectiveness of our combined model, we conducted a psychophysical experiment in a controlled laboratory environment with young (18-31 y.o.), middle-aged (32-52 y.o.), and older (53+ y.o.) adults, measuring their image quality preferences for 84 test images. Our analysis shows that the predictions by our age-specific IQA metric are well correlated with the collected subjective IQA results from our psychophysical experiment.
Caustics projected onto the surface carry very interesting information regarding the material they are cast by. It has been observed in previous studies that caustics could be a widely used cue for translucency assessment by human subjects. We hypothesize that changing the reflectance properties of the surface an object is placed on, and removal of the caustic pattern might impact perceived translucency of the material. We conducted psychophysical experiments to investigate the correlation among caustics, environment colors and translucency perception, and found very interesting indications that materials appear less translucent under the conditions where caustics are absent.