Paper
24 January 2012 Detection of backlight images using chrominance
Author Affiliations +
Proceedings Volume 8292, Color Imaging XVII: Displaying, Processing, Hardcopy, and Applications; 82920J (2012) https://doi.org/10.1117/12.906114
Event: IS&T/SPIE Electronic Imaging, 2012, Burlingame, California, United States
Abstract
An image taken under the backlight condition shows that a main object or foreground appears very dark, but a background appears relatively bright since the exposure time of the main object or foreground is relatively shorter than the one of the background due to high luminance from the background. The determination of the backlight image is generally done by luminance histogram analysis since it is believed that the distinct characteristic of the backlight image is a large luminance difference between the foreground and background. However, this conventional detection method may not be adequate for video images since it generally targets on still images. Furthermore, the detection of the backlight image would not be performed well if there are abrupt changes in light, motion, or scenes. Inaccurate detection leads to unnecessary compensation that makes images over-highlighted or flickered, especially when consecutive frames of video have different illumination modes. Since an image taken under normal light conditions may also have the similar luminance characteristics of the backlight image, it would not be sufficient to discriminate between the normal light and backlight image using only luminance information. Therefore, the analysis of chrominance of images is introduced to detect the backlight image more accurately.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hyung Jun Park and Seong Wook Han "Detection of backlight images using chrominance", Proc. SPIE 8292, Color Imaging XVII: Displaying, Processing, Hardcopy, and Applications, 82920J (24 January 2012); https://doi.org/10.1117/12.906114
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KEYWORDS
Chromium

Video

Detection and tracking algorithms

Target detection

Digital cameras

Ranging

Fuzzy logic

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