Style-based tone mapping for HDR images

In this paper we propose a different approach to high dynamic range (HDR) image tone mapping. We put away the assumption that there is a single optimal solution to tone mapping. We argue that tone mapping is inherently a personal process that is guided by the taste and preferences of the artist; different artists can produce different depictions of the same scene. However, most existing tone mapping operators (TMOs) compel the artists to produce similar renderings. Operators that give more freedom to artists require adjustment of many parameters which turns tone mapping into a laborious process. In contrast to these, we propose an algorithm which learns the taste and preferences of an artist from a small set of calibration images. Any new image is then tone mapped to convey the appearance that would be desired by the artist.