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Error propagation analysis in color measurement and imaging
Author(s) -
Burns Peter D.,
Berns Roy S.
Publication year - 1997
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/(sici)1520-6378(199708)22:4<280::aid-col9>3.0.co;2-l
Subject(s) - mathematics , covariance , color difference , propagation of uncertainty , colorimeter , color correction , artificial intelligence , icc profile , algorithm , statistics , computer science , computer vision , color image , image processing , optics , image (mathematics) , physics , enhanced data rates for gsm evolution
We apply multivariate error‐propagation analysis to color‐signal transformations. Results are given that indicate how linear, matrix, and nonlinear transformations influence the mean, variance, and covariance of color‐measurements and color‐images. Since many signal processing paths include these steps, the analysis is applicable to color‐measurement and imaging systems. Expressions are given that allow image noise or error propagation for a spectrophotometer, colorimeter, or digital camera. In a computed example, error statistics are propagated from tristimulus values to CIELAB coordinates. The resulting signal covariance is interpreted in terms of CIELAB error ellipsoids and the mean value of color‐difference measures, $\Delta \rm{E}^{*}_{\hbox{ab}}$ and $\Delta \rm{E}^{*}_{94}$ . The application of this analysis to system design is also illustrated by relating a $\Delta \rm{E}^{*}_{94}$ tolerance to equivalent tristimulus‐value error statistics. © 1997 John Wiley & Sons, Inc. Col Res Appl, 22, 280–289, 1997