Robustified Least Squares for Spectrum Neugebauer Model

HAN Fang-fang, LI Li-xia, ZHANG Yi-xin

Packaging Engineering ›› 2011 ›› Issue (21) : 106-109.

Packaging Engineering ›› 2011 ›› Issue (21) : 106-109.

Robustified Least Squares for Spectrum Neugebauer Model

  • HAN Fang-fang, LI Li-xia, ZHANG Yi-xin
Author information +
History +

Abstract

Yule-Nielsen modified spectrum Neugebauer model is an important spectrum prediction model in predicting color output of color halftone prints. In order to improve the prediction accuracy, spectrum Neugebauer model and robustified estimation theory were analyzed and a method of robustified least squares to estimate dot area function and primary spectrum reflectance were put forward. Commonly used robust estimation programs are Huber estimation and IGG estimation. Experiment results showed that compared to traditional least squares (LS) based methods, the accuracy of spectrum Neugebauer model with RLS approach is higher and more stable under the condition of gross error.

Cite this article

Download Citations
HAN Fang-fang, LI Li-xia, ZHANG Yi-xin. Robustified Least Squares for Spectrum Neugebauer Model[J]. Packaging Engineering. 2011(21): 106-109

Accesses

Citation

Detail

Sections
Recommended

/