By Topic

A printer model using signal processing techniques

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Vongkunghae, A. ; MRC Inst., Univ. of Idaho, Moscow, ID, USA ; Jang Yi ; Wells, R.B.

An accurate printer model that is efficient enough to be used by halftoning algorithms is proposed. The proposed signal processing model (SPM) utilizes a physical model to train adaptive linear combiners (ALCs), after which the average exposure of each subpixel for any input pattern can be calculated using the optimized weight vector. The SPM can be used to model multi-level halftoning and resolution enhancement, as well as traditional halftoning. The SPM is comprised of a single ALC layer followed by a peak-to-average ratio (PAR) correction layer, which serves to produce a PAR of less than 1.5 in the modeled exposure. The PCN (PAR correction network) employs one ALC/pixel and exploits the physics governing the characteristics of exposure in small regions. A relatively small number of training patterns suffices to train the SPM.

Published in:

Image Processing, IEEE Transactions on  (Volume:12 ,  Issue: 7 )