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19 February 2018 A fast color cast detection and correction method for large-field video-image in nature scene
Ke Hong, Yu Shi, Xia Hua
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Proceedings Volume 10607, MIPPR 2017: Multispectral Image Acquisition, Processing, and Analysis; 1060702 (2018) https://doi.org/10.1117/12.2283209
Event: Tenth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2017), 2017, Xiangyang, China
Abstract
Color cast is a major problem of target detection and recognition base on image feature analysis. A color cast detection and correction algorithm for video-image in nature scene is proposed in this paper. To overcome the inaccurate detection in existed color cast detection method based on RGB space, the analysis method based on the color distribution characteristics of the equivalent circle in Lab space is proposed. In order to achieve better color correction results, the gray balance and perfect reflection method is combined to reproduce the actual color of the objects, especially a modified method for images with severe color deviation. Experimental results show that the proposed methods can detect the degree of color cast correctly, achieve better correction results, and meet the real-time requirements.
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Ke Hong, Yu Shi, and Xia Hua "A fast color cast detection and correction method for large-field video-image in nature scene", Proc. SPIE 10607, MIPPR 2017: Multispectral Image Acquisition, Processing, and Analysis, 1060702 (19 February 2018); https://doi.org/10.1117/12.2283209
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KEYWORDS
Video
Image processing
RGB color model
Detection and tracking algorithms
Image analysis
Video surveillance
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