Spectral Sharpening and the Bradford Transform

The Bradford chromatic adaptation transform, empirically derived by Lam, models illumination change. Specifically, it provides a means of mapping XYZs under a reference source to XYZs for a target light such that the corresponding XYZs produce the same perceived colour. One implication of the Bradford chromatic adaptation transform is that colour correction for illumination takes place not in cone space but rather in a ‘narrowed’ cone space. The Bradford sensors have their sensitivity more narrowly concentrated than the cones. However, Bradford sensors are not optimally narrow. Indeed, recent work has shown that it is possible to sharpen sensors to a much greater extent than Bradford. The focus of this paper is comparing the perceptual error between actual appearance and predicted appearance of a colour under different illuminants, since it is perceptual error that the Bradford transform minimizes. Lam’s original experiments are revisited and perceptual performance of the Bradford transform is compared with that of a new adaptation transform that is based on sharp sensors. Results were found to be similar for the two transforms. In terms of CIELAB error, Bradford performs slightly better. But in terms of the more accurate CIELAB 94 and CMC colour difference formulae, the sharp transform performs equally well: there is no statistically significant difference in performance.