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Spectral‐based color separation using linear regression iteration
Author(s) -
Urban Philipp,
Grigat RolfRainer
Publication year - 2006
Publication title -
color research and application
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.393
H-Index - 62
eISSN - 1520-6378
pISSN - 0361-2317
DOI - 10.1002/col.20211
Subject(s) - simple (philosophy) , affine transformation , separation (statistics) , convergence (economics) , mathematics , algorithm , matrix (chemical analysis) , sequence (biology) , spectrum (functional analysis) , computer science , statistics , pure mathematics , philosophy , materials science , physics , epistemology , quantum mechanics , biology , economics , composite material , genetics , economic growth
The present article will introduce a very simple new method for spectral‐based color separation. This method inverts a Yule–Nielsen modified spectral Neugebauer model, utilizing its affine multilinearity in the 1/n‐space. By means of linear regression, a sequence of colorant combinations is constructed converging to a colorant combination that approximates the desired reflectance spectrum in the sense of the smallest RMS error. Each iteration step consists mainly of two simple matrix–vector multiplications. With the aid of various simulation experiments, investigations on the speed of convergence are conducted. © 2006 Wiley Periodicals, Inc. Col Res Appl, 31, 229–239, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20211