Shaped local regression and its application to color transforms

Vishal Monga, Raja Bala

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Scopus citations

    Abstract

    Local linear regression is widely used in describing input-output relationships and has been applied with reasonable success to computational problems in color imaging such as approximating printer-models and device color characterization transforms. A popular flavor of local regression is one where locality is achieved by using a weight function which decays as a function of the distance from the regression data point. This paper proposes an improved method for local regression by introducing the notion of "shaping" in the localizing weight function. We make two novel contributions: I) a parameterization of the regression weight function via a shaping matrix, and 2) a method to optimize shape by explicitly introducing the shaping matrix parameters in the regression error measure. Experiments reveal dramatic improvements in approximating printer color transforms by using shaped local linear regression. A particularly pronounced benefit is gained in the case of sparse training sets, which are fairly common in color characterization applications due to the effort and/or cost associated with acquiring color measurements.

    Original languageEnglish (US)
    Title of host publication17th Color Imaging Conference
    Subtitle of host publicationColor Science and Engineering Systems, Technologies, and Applications - Final Program and Proceedings
    Pages272-277
    Number of pages6
    StatePublished - Dec 1 2009
    Event17th Color Imaging Conference: Color Science and Engineering Systems, Technologies, and Applications - Albuquerque, NM, United States
    Duration: Nov 9 2009Nov 13 2009

    Publication series

    NameFinal Program and Proceedings - IS and T/SID Color Imaging Conference
    ISSN (Print)1083-1304

    Other

    Other17th Color Imaging Conference: Color Science and Engineering Systems, Technologies, and Applications
    CountryUnited States
    CityAlbuquerque, NM
    Period11/9/0911/13/09

    All Science Journal Classification (ASJC) codes

    • Electronic, Optical and Magnetic Materials
    • Atomic and Molecular Physics, and Optics

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