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Iteratively Clustered Interpolation (ICI) Algorithm for Geometrical Interpolation of an Irregularly Spaced Multidimensional Color Space

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A printer inverse map is usually represented as a multivariable lookup table, associating points in the printer's output color space with points in the printer's input color space. This lookup table is an essential component in many print quality enhancement algorithms. It is often desirable to have a printer inverse table with input nodes regularly spaced on a sequential plane. Thus, the computation of this lookup table requires the interpolation of irregularly sampled multidimensional data, coming from experiments used to determine the printer forward map. Existing computational techniques do not provide an accurate printer inverse map from irregularly sampled data. In this paper we introduce a new Iteratively Clustered Interpolation (ICI) algorithm to compute an accurate inverse table from irregularly sampled color data. This algorithm is based on a gradient optimization method with initial points generated through a novel iterative technique. Experimental results are included to show the effectiveness of this algorithm in comparison with other techniques.

Document Type: Research Article

Publication date: January 1, 2000

More about this publication?
  • For more than 25 years, NIP has been the leading forum for discussion of advances and new directions in non-impact and digital printing technologies. A comprehensive, industry-wide conference, this meeting includes all aspects of the hardware, materials, software, images, and applications associated with digital printing systems, including drop-on-demand ink jet, wide format ink jet, desktop and continuous ink jet, toner-based electrophotographic printers, production digital printing systems, and thermal printing systems, as well as the engineering capability, optimization, and science involved in these fields.

    Since 2005, NIP has been held in conjunction with the Digital Fabrication Conference.

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