Skip to main content
padlock icon - secure page this page is secure

Automatic Compensation for Camera Settings for Images Taken under Different Illuminants

Buy Article:

$17.00 + tax (Refund Policy)

The combination of two images shot for the same scene but under different illumination has been used in wide applications ranging from estimating scene illumination, to enhancing photographs shot in dark environments, to shadow removal. An example is the use of a pair of images shot with and without a flash. However, for consumer-grade digital cameras, due to the different illumination conditions the two images usually have different camera settings when they are taken, such as exposure time and white balance. Thus adjusting (registering) the two images becomes a necessary step prior to combining the two images. Unfortunately, how to register these two images has not been investigated fully. In this paper, we propose a method which can parametrically adjust the two images so as to compensate for the difference in exposure speed, ISO, aperture size, and white balance. This is accomplished by training a 2nd-order masking model on a set of image pairs to predict the model parameters. This trained model can then be used to register two images. In the training phase, we wish to develop a scheme for adjusting the magnitude in each color channel of one image to register with the other image, for each image pair. The problem is difficult because the difference between the two images is a composite of both camera settings and illumination. Here, we use the simple fact that a shadow effect should be caused purely by the changes of illumination. Suppose we have two images, one of which is taken under illuminant 1 and the other is taken under illuminant 1 plus illuminant 2. If we subtract the first image from the second, a shadow caused by illuminant 1 should disappear in the resulting difference. By adjusting the RGB pixel values of one image so as to completely remove the shadow in the difference image, compensating magnitudes for each color channel can be computed and used to train a masking model. This masking model can then accurately compensate for camera settings for any two new images such that the difference between compensated images reflects only the difference in illumination.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Document Type: Research Article

Publication date: January 1, 2006

More about this publication?
  • CIC is the premier annual technical gathering for scientists, technologists, and engineers working in the areas of color science and systems, and their application to color imaging. Participants represent disciplines ranging from psychophysics, optical physics, image processing, color science to graphic arts, systems engineering, and hardware and software development. While a broad mix of professional interests is the hallmark of these conferences, the focus is color. CICs traditionally offer two days of short courses followed by three days of technical sessions that include three keynotes, an evening lecture, a vibrant interactive (poster) papers session, and workshops. An endearing symbol of the meeting is the Cactus Award, given each year to the author(s) of the best interactive paper; there are also Best Paper and Best Student Paper awards.

    Please note: for Purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual paper for details.

  • Information for Authors
  • Submit a Paper
  • Subscribe to this Title
  • Membership Information
  • Terms & Conditions
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more