Evaluating the Performance of Polynomial Regression Method with Different Parameters during Color Characterization | Zendy

Bangyong Sun | Zendy; Han Liu | Zendy; Shisheng Zhou | Zendy; Wenli Li | Zendy

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Evaluating the Performance of Polynomial Regression Method with Different Parameters during Color Characterization

Author(s) -

Bangyong Sun,

Han Liu,

Shisheng Zhou,

Wenli Li

Publication year - 2014

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2014/418651

Subject(s) - polynomial regression , polynomial , wilkinson's polynomial , mathematics , rgb color model , reciprocal polynomial , color space , matrix polynomial , computation , linearization , monic polynomial , regression analysis , algorithm , mathematical analysis , computer science , artificial intelligence , statistics , nonlinear system , image (mathematics) , physics , quantum mechanics

The polynomial regression method is employed to calculate the relationship of device color space and CIE color space for color characterization, and the performance of different expressions with specific parameters is evaluated. Firstly, the polynomial equation for color conversion is established and the computation of polynomial coefficients is analysed. And then different forms of polynomial equations are used to calculate the RGB and CMYK’s CIE color values, while the corresponding color errors are compared. At last, an optimal polynomial expression is obtained by analysing several related parameters during color conversion, including polynomial numbers, the degree of polynomial terms, the selection of CIE visual spaces, and the linearization

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