Showing papers by "Gaurav Sharma published in 1999"

End-to-end color printer calibration by total least squares regression

Abstract: Neugebauer (1937) modeling plays an important role in obtaining end-to-end device characterization profiles for halftone color printer calibration. This paper proposes total least square (TLS) regression methods to estimate the parameters of various Neugebauer models. Compared to the traditional least squares (LS) based methods, the TLS approach is physically more appropriate for the printer modeling problem because it accounts for errors in the measured reflectance of both the primaries and the modeled samples. A TLS method based on print measurements from single-colorant step-wedges is first developed. The method is then extended to incorporate multicolorant print measurements using an iterative algorithm. The LS and TLS techniques are compared through tests performed on two color printers, one employing conventional rotated halftone screens and the other using a dot-on-dot halftone screen configuration. Our experiments indicate that the TLS methods yield a consistent and significant improvement over the LS-based techniques for model parameter estimation. The gains from the TLS method are particularly significant when the number of patches for which measured data is available is limited.

Printer characterization adjustment for different papers

Abstract: A method of adjusting an image production system to account for a variable property of a desired output medium includes storing a reference characterization of at least one measured value associated with a reference output medium. An output value, adjusted for the variable property of the desired output medium, is determined based on data including the reference characterization of the reference output medium, for example stored in color lookup tables, color rendering dictionaries, or the like. Based on the adjusted output value determined, the desired output medium is then printed or otherwise marked using the output value.

Model-based spectral calibration of color scanners

Abstract: A target-less calibration system for calibrating a scanner for a particular input medium without using a dedicated calibration target on that medium is disclosed. The system employs the (predetermined) spectral response of the scanner and representative spectral measurements of the input medium to achieve the calibration. The representative spectral measurements of the input medium are used to infer the set of feasible spectra for the medium. Corresponding to a given scanner signal output, another set representing the candidate spectra that could have resulted in the given scanner output are determined using the predetermined scanner spectral response. Combining the two requirements, a spectrum in the intersection of the thus determined sets of scanner candidate spectra and prenoted feasible media spectra provides an estimated spectrum of the input sample. Repeating the process over the range of scanner outputs provides a complete spectral calibration for the scanner for the given medium. Each spectrum is convertible to a device-independent color space for any given viewing illuminant, providing a calibration from the scanner output to device independent color space.

Show-through compensation apparatus and method

Abstract: Apparatus and methods that adjust image data for show-through image information of an image on a front side of an image bearing substrate having image data on a back side and on an adjacent side of a backing substrate, e.g., the pages of a bound volume. Image data for a front side image, a back side image and an adjacent side image is obtained from an optical sensor that senses light reflected from the image bearing substrate. The image data is stored in a memory and is used to determine scanned density data and approximate absorbency data for the respective sides of the substrates. Show-through compensated density data for the front side image is computed by filtering the absorbency data for the back and adjacent side with a filter characteristic of the show-through characteristics of the image bearing substrate and subtracting this filtered absorbency data from the front side scanned density data. If required, the show-through compensated density data for the front, side image is converted into a show-through compensated reflectance image.

Methods and apparatus for identifying marking process and modifying image data based on image spatial characteristics

Abstract: A marking process used to mark an image on a substrate, such as a photographic marking process, a lithographic marking process, an ink-jet marking process, a line-on-line xerographic marking process or a rotated-screen xerographic marking process, is automatically detected using at least one image spatial characteristic obtained from image information picked up from the image. The at least one spatial characteristic, which is unique to the type of marking process, is obtained, for example, by generating an image power spectrum and analyzing the power spectrum according to the existence, position, and/or color of spectral peaks, and/or the existence or absence of abnormally high energy at the high frequencies in the power spectrum.

Target-less Scanner Color Calibration.

Abstract: The lack of a scanner calibration target representative of the image medium (substrate and colorants) often limits the accuracy of scanner color calibration. In this paper, a color calibration method is presented for photographic input media that does not require a calibration target. Using characteristic spectral measurements from the image(s) to be scanned, a model for the spectra on the medium is obtained through a principal component analysis. The spectral sensitivity of the scanner provides a model for its operation. By using a set-theoretic estimation method that combines the models for the scanner and the medium, the spectral reflectance of the input corresponding to a given set of scanner RGB values can be determined. This provides a spectral calibration for the scanner, which can readily be transformed into a color calibration under any suitable viewing illuminant. Results from simulations and actual calibrations demonstrate the value of the new method.

Methods and apparatus for modifying image data based on identification of marking process

Abstract: Image information is re-calibrated based on the type of marking process and materials by which the image corresponding to the image information was marked on a substrate. The marking process is automatically detected by using, for example, at least one spatial characteristic obtained from the image information.