Purkinje Images: Conveying Different Content for Different Luminance Adaptations in a Single Image

Providing multiple meanings in a single piece of art has always been intriguing to both artists and observers. We present Purkinje images, which have different interpretations depending on the luminance adaptation of the observer. Finding such images is an optimization that minimizes the sum of the distance to one reference image in photopic conditions and the distance to another reference image in scotopic conditions. To model the shift of image perception between day and night vision, we decompose the input images into a Laplacian pyramid. Distances under different observation conditions in this representation are independent between pyramid levels and pixel positions and become matrix multiplications. The optimal pixel colour can be found by inverting a small, per-pixel linear system in real time on a GPU. Finally, two user studies analyze our results in terms of the recognition performance and fidelity with respect to the reference images.