Recovering high dynamic range radiance maps from photographs

TLDR

The paper proposes a method to recover high‑dynamic‑range radiance maps from photographs taken with standard imaging equipment. The method captures multiple exposures, estimates the camera response function via reciprocity, and fuses the images into a high‑dynamic‑range radiance map. The approach successfully produces radiance maps proportional to true scene radiance, enabling applications such as realistic motion blur and visual‑system simulation in graphics.

Abstract

We present a method of recovering high dynamic range radiance maps from photographs taken with conventional imaging equipment. In our method, multiple photographs of the scene are taken with different amounts of exposure. Our algorithm uses these differently exposed photographs to recover the response function of the imaging process, up to factor of scale, using the assumption of reciprocity. With the known response function, the algorithm can fuse the multiple photographs into a single, high dynamic range radiance map whose pixel values are proportional to the true radiance values in the scene. We demonstrate our method on images acquired with both photochemical and digital imaging processes. We discuss how this work is applicable in many areas of computer graphics involving digitized photographs, including image-based modeling, image compositing, and image processing. Lastly, we demonstrate a few applications of having high dynamic range radiance maps, such as synthesizing realistic motion blur and simulating the response of the human visual system.