Enhancing Printer Imaging Systems Performance
20 February, 2017 -
16:00 to 17:00
Dr. Puneet Goyal
Printing industry is estimated at about $230 billion/year worldwide in revenue. Printing employs the process of halftoning i.e. transforming a continuous-tone image into an image with a limited number of tone levels. Direct binary search (DBS) is an iterative halftoning algorithm, considered as gold standard for generating best dispersed-dot halftones but it does not account well for printer-dots development and neighborhood dot interactions in electro-photographic (EP) printers. We developed an innovative and efficient strategy using least squares to estimate the impact of larger neighborhood pixels on central pixel absorptance, and incorporated this measurement-based stochastic-model for dot-interactions within the DBS framework. Experimental results show that the proposed EP-model based approach has reduced the tone-prediction error and also improved the print quality, reducing the mottle and banding artifacts. Most EP printers prefer stochastic clustered-dot halftone textures for rendering smooth and stable prints, and for avoiding moiré artifacts. But there are no standard print quality assessment measures that can be easily used for quantitatively evaluating and comparing different stochastic clustered-dot halftoning methods. We proposed a new compactness measure that seems good metric to quantitatively compare and assess the print quality of different stochastic clustered-dot halftoning methods. Comparison results using this newly proposed metric are almost in agreement with psychophysical experiments results reported earlier.