| Paper: | MP-L6.1 |
| Session: | Image Scanning, Display, Printing, Color and Multispectral Processing I |
| Time: | Monday, September 17, 14:30 - 14:50 |
| Presentation: |
Lecture
|
| Title: |
COLOR MANAGEMENT OF PRINTERS BY REGRESSION OVER ENCLOSING NEIGHBORHOODS |
| Authors: |
Erika Chin; University of Virginia | | |
| | Eric Garcia; University of Washington | | |
| | Maya Gupta; University of Washington | | |
| Abstract: |
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. |
