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Parameter Optimized Simple Matrix Color Device Model for Liquid Crystal Display Monitors

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A parameter optimized simple matrix (POSM) model is proposed for characterizing the liquid crystal display (LCD) monitor with variant primary chromaticity and primary crosstalk. This method is the same as the conventional simple matrix (CSM) model except that black point, white point, one-primary measurement data, and two primary measurement data are taken as the training samples for optimizing the signal nonlinear transformations (SNTs) and chromaticity matrix. As the configuration of the POSM model is the same as the CSM model, its backward model is simple and can be implemented for video applications. Polynomial function is taken as the SNT. The optimization process comprises the simulated annealing method for optimizing the coefficients of SNTs and the regression method for calculating the chromaticity matrix. The results show that the average color difference (CIEDE2000) of 224 random test samples for two characterized LCD monitors are 2.02 and 1.33 with a forward POSM model, and are 2.32 and 1.27 with a backward POSM model. The primary crosstalk of the LCD monitor with a higher average color difference is more serious than the other monitor. The performance of the POSM model is much better than the CSM model. For the monitor with lower crosstalk, the POSM model is better than the three-dimensional look-up table (3D-LUT) model with a 5 × 5 × 5 lattice but is worse than the 3D-LUT model with a 8 × 8 × 8 lattice.

Document Type: Research Article


Affiliations: Institute of Electrical Engineering, Chung Hua University, 30 Tung Shiang, Hsinchu, Taiwan, Republic of China

Publication date: 2006-01-01

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  • The Journal of Imaging Science and Technology (JIST) is dedicated to the advancement of imaging science knowledge, the practical applications of such knowledge, and how imaging science relates to other fields of study. The pages of this journal are open to reports of new theoretical or experimental results, and to comprehensive reviews. Only original manuscripts that have not been previously published, nor currently submitted for publication elsewhere, should be submitted.

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