Quantigraphic Imaging: Estimating the camera response and exposures from
differently exposed images
Steve Mann
University of Toronto, Dept. E.C.E.
Toronto, Ontario, Canada, M5S 3G4
and
Richard Mann
Dept. C.S.
University of Waterloo
ABSTRACT:
Multiple differently exposed pictures of the same subject matter arise
naturally whenever a video camera having automatic exposure
captures multiple frames of video with the same subject matter appearing
in regions of overlap between at least some of the successive video frames.
Almost all cameras have some kind of automatic exposure feature.
Generally automatic exposure is center weighted, so that when a light
object falls in the center of the frame the exposure is automatically
decreased, whereas the exposure is automatically increased when the camera
swings around to point at a darker object.
In this paper, it is assumed that the spatial (e.g. projective)
coordinate transformation between successive frames of the sequence is known
(or equivalently that it is the identity), and the contribution of the paper
is an efficient way to estimate the tonal relationship between successive
frames of the sequence. In particular methods are proposed to simultaneously
estimate the unknown camera response function, as well as the set of unknown
relative exposure changes among images, up to a single unknown scalar constant.
The method comprises a succession of guesses each of which is a refinement
of the previous. The first guess is often sufficient,
so that no initial solution needs to be provided by the user.
Each subsequent guess is a least squares solution
so that no computationally expensive optimization is required.
Since the method makes use of all the data, it is extremely immune to noise.
The method is tested against state-of-the art laboratory measurement
instruments to confirm the accuracy of the results.
KEYWORDS:
Comparametric Equations, Quantimetric Imaging, Photoquantity,
Dynamic Range, Automatic Gain Control (AGC), Extended Response