Recovering High Dynamic Range Radiance Maps from Photographs
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 asingle, 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.