Paper
24 April 2002 New approach to auto-white-balancing and auto-exposure for digital still cameras
Nasser Kehtarnavaz, Hyuk-Joon Oh, I. Shidate, Youngjun F. Yoo, R. Taluri
Author Affiliations +
Abstract
This paper presents an auto-white balancing algorithm named scoring. The spectral distributions of the Macbeth reference colors together with the spectral distributions of various color temperature light sources are used to obtain a number of reference color points in the CbCr color space. A number of representative color points are also obtained from a captured image by using a previously developed multi-scale clustering algorithm. A match is then established between the set of reference colors and the set of representative colors. The matching scheme generates the most likely light source candidate under which the image is taken. Furthermore, this paper presents an auto-exposure algorithm using a mapping from the luminance histograms of five sub- areas in the image to an exposure value. A neural network is designed to perform the mapping. The histogram in each sub- area is used to determine the mean, variance, minimum, and maximum luminance for that sub-area. The same spatial information is computed for previous frames to incorporate temporal changes in luminance into the network.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Nasser Kehtarnavaz, Hyuk-Joon Oh, I. Shidate, Youngjun F. Yoo, and R. Taluri "New approach to auto-white-balancing and auto-exposure for digital still cameras", Proc. SPIE 4669, Sensors and Camera Systems for Scientific, Industrial, and Digital Photography Applications III, (24 April 2002); https://doi.org/10.1117/12.463431
Lens.org Logo
CITATIONS
Cited by 4 scholarly publications and 2 patents.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Cameras

Light sources

Neural networks

Camera shutters

Digital cameras

Algorithm development

Prototyping

Back to Top