A popular color management standard for controlling color reproduction is the ICC color profile. The core of the ICC profile is a look-up-table which maps a regular grid of device-independent colors to the printer colorspace. To estimate the look-up-table from sample input-output colors, local linear regression has been shown to work better than other methods. An open problem in local linear regression is how to define the locality or neighborhood for each of the local linear regressions. In this paper, new adaptive neighborhood definitions and regularized local linear regression are proposed to address this problem. The adaptive neighborhood definitions enclose the test sample, and are motivated by a result showing they yield bounded estimation variance. An experiment shows that both regularization and the proposed neighborhoods can lead to a significant reduction in error.
[1]
Maya R. Gupta.
Custom color enhancements by statistical learning
,
2005,
IEEE International Conference on Image Processing 2005.
[2]
Chris Murphy,et al.
Real World Color Management
,
2003
.
[3]
A. D. Gordon,et al.
Interpreting multivariate data
,
1982
.
[4]
Kei Takeuchi,et al.
Interpreting Multivariate Data@@@The Foundations of Multivariate Analysis
,
1983
.
[5]
Arthur E. Hoerl,et al.
Ridge Regression: Biased Estimation for Nonorthogonal Problems
,
2000,
Technometrics.
[6]
Henry R. Kang.
Color Technology for Electronic Imaging Devices
,
1997
.