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http://dx.doi.org/10.5573/ieek.2013.50.10.142

Spectral Reflectance Estimation based on Similar Training Set using Correlation Coefficient  

Yo, Ji-Hoon (School of Electronics Engineering, Kyungpook National University)
Ha, Ho-Gun (School of Electronics Engineering, Kyungpook National University)
Kim, Dae-Chul (School of Electronics Engineering, Kyungpook National University)
Ha, Yeong-Ho (School of Electronics Engineering, Kyungpook National University)
Publication Information
Journal of the Institute of Electronics and Information Engineers / v.50, no.10, 2013 , pp. 142-149 More about this Journal
Abstract
In general, a color of an image is represented by using red, green, and blue channels in a RGB camera system. However, only information of three channels are limited to estimate a spectral reflectance of a real scene. Because of this, the RGB camera system can not accurately represent the color. To overcome this limitation and represent an accurate color, researches to estimate the spectral reflectance by using a multi-channel camera system are being actively proceeded. Recently, a reflectance estimation method adaptively constructing a similar training set from a traditional training set according to a camera response by using a spectral similarity was introduced. However, in this method, an accuracy of the similar training set is reduced because the spectral similarity based on an average and a maximum distances was applied. In this paper, a reflectance estimation method applied a spectral similarity based on a correlation coefficient is proposed to improve the accuracy of the similar training set. Firstly, the correlation coefficient between the similar training set and the spectral reflectance obtained by Wiener estimation method is calculated. Secondly, the similar training set is constructed from the traditional training set according to the correlation coefficient. Finally, Wiener estimation method applied the similar training set is performed to estimate the spectral reflectance. To evaluate a performance of the proposed method with previous methods, experimental results are compared. As a result, the proposed method showed the best performance.
Keywords
Multispectral imaging; Wiener estimation method; Reflectance;
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