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Reduction of Color Distortion by Estimating Dominant Chromaticity in Multi-Scaled Retinex  

Jang, In-Su (School of Electrical Engineering and Computer Science, Kyungpook National University)
Park, Kee-Hyon (School of Electrical Engineering and Computer Science, Kyungpook National University)
Ha, Yeong-Ho (School of Electrical Engineering and Computer Science, Kyungpook National University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.46, no.3, 2009 , pp. 52-59 More about this Journal
Abstract
In general, methods based on histogram or a correction of gamma curve are usually utilized to enhance the contrast of captured image in the dark scene. These methods are efficient to enhance the contrast globally, however, they locally induced the low quality of image. Recently, to resolve the problem, the multi-scaled refiner algorithm improving the contrast with locally averaged lightness is proposed. However, estimating the locally averaged lightness, if there is the object with a high saturated color, the color distortion might be induced by the color of object. Thus, in this paper, the dominant chromaticity of image is estimated to correct the locally averaged lightness in multi-scaled retinex algorithm. Because the average chromaticity of image includes the chromaticity of illumination, the dominant chromaticity is estimated with dividing the average chromaticity of image by the estimated chromaticity of illumination from highlight region. In addition, to improve the lower chroma by multi-scaled retinex algorithm generally, the chroma was compensated preserving the hue in the CIELAB color space.
Keywords
Retinex;
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