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Proceedings Paper

Pseudo-color coding method of infrared images based on human vision system
Author(s): Xiao Zhang; Tingzhu Bai; Hailan Li
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Paper Abstract

Infrared images often display in gray scale. The low contrast and the unclear visual effect are the most notable characters of infrared images that make difficult to observe. It is a fact that gray scale is not sensitive to human eyes, and it has only 60 to 90 just noticeable differences (JNDs). In comparison with gray scale, color scale might give up to 500 JNDs. Usually people can distinguish many kinds of colors much more than grays. And in gray images, human don't have the ability to tell apart the nuances about detail. Pseudo-color coding enhancement is the task of applying certain alterations to an input gray-image such as to obtain color-image that is a more visually pleasing. In this paper, we introduced a pseudo-color coding method based on human vision system for infrared images display. The HSI space is especially fit for human vision system and is viewed as an approximation of perceptual color space. So the pseudo-color coding method introduced is based on HSI space. In the first place, the individual functional relationship of Hue, Intensity, and Saturation with gray scale level is established. In the second place, the corresponding RGB values are obtained through transformation from the HSI color space to the RGB space. Lastly, the effect of Infrared images enhancement based on the pseudo-color coding method is displayed. Results indicate that this method is superior to other methods through the comparison.

Paper Details

Date Published: 8 January 2008
PDF: 8 pages
Proc. SPIE 6835, Infrared Materials, Devices, and Applications, 68351N (8 January 2008); doi: 10.1117/12.756471
Show Author Affiliations
Xiao Zhang, Beijing Institute of Technology (China)
Tingzhu Bai, Beijing Institute of Technology (China)
Hailan Li, Beijing Institute of Technology (China)


Published in SPIE Proceedings Vol. 6835:
Infrared Materials, Devices, and Applications
Yi Cai; Haimei Gong; Jean-Pierre Chatard, Editor(s)

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