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Wavelet Analysis and Modeling of Time-Varying TRCs

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Abstract:

The tone reproduction curve (TRC) is a representation of a printer's input-output mapping for each primary color. It is a two dimensional signal with both temporal and tonal characteristics. With an appropriate signal model that represents the TRC, the entire time-varying TRC can be reconstructed from measurements of a few time-sequential scheduled print patches. The reconstructed TRC can then be used as feedback signal for control systems to compensate for any TRC variations. In the past, signal models based on Fourier basis and principal components analysis have been proposed for the design and analysis of the sampling sequence and the reconstruction filter. However, the tone reproduction has localized features in that it variation is less at some tones than at others. These features have not been exploited in previous signal models but can potentially improve the effectiveness of sampling and reconstruction algorithms. In this paper, the localized nature of wavelets is used to capture the ápriori knowledge of these local features and a wavelet based representation of the time-varying TRC is proposed. The wavelet based model is obtained from a track of experimentally obtained time-varying TRC data. The usefulness of this approach is demonstrated from the reconstruction of a time-sequentially sampled TRC.

Document Type: Research Article

Publication date: January 1, 2011

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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