doi: 10.4304/jsw.7.6.1187-1194
Image Enhancement Based on Selective - Retinex Fusion Algorithm
2College of Informatics and Electronics, Zhejiang Sci-Tech University, Hangzhou, China
Abstract—The brightness adjustment method for the night-vision image enhancement is considered in this paper. The color RGB night-vision image is transformed into an uncorrelated color space--- the YUV space. According to the characteristics of the night-vision image, we develop the modified Retinex algorithm based on the S curve firstly, by which the luminance component is enhanced and the brightness of the night-vision image is effectively improved. Then the luminance component of source image is enhanced by the selective and nonlinear gray mapping to retain the essential sunlight and shade information. Based on the two enhancement images, the night-vision image with enough bright and necessary sunlight and shade information is combined by the weighted parameter. According to experimental results, the night-vision image obtained is very fit for the visual observation.
Index Terms—image enhancement, night-vision image, Retinex, the S curve, selective and nonlinear gray mapping
Cite: Xuebo Jin, Jia Bao, and Jingjing Du, "Image Enhancement Based on Selective - Retinex Fusion Algorithm," Journal of Software vol. 7, no. 6, pp. 1187-1194, 2012.
General Information
ISSN: 1796-217X (Online)
Abbreviated Title: J. Softw.
Frequency: Quarterly
APC: 500USD
DOI: 10.17706/JSW
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Cecilia Xie
Abstracting/ Indexing: DBLP, EBSCO,
CNKI, Google Scholar, ProQuest,
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