A printer model using signal processing techniques

Author

Vongkunghae, Akaraphunt ; Yi, Jang ; Wells, Richard B.

Author_Institution

MRC Inst., Univ. of Idaho, Moscow, ID, USA

Volume

12

Issue

7

fYear

2003

fDate

7/1/2003 12:00:00 AM

Firstpage

776

Lastpage

783

Abstract

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.

Keywords

electrophotography; image enhancement; image resolution; laser printers; learning (artificial intelligence); printing; adaptive linear combiners; electrophotography; halftoning algorithms; multi-level halftoning; peak-to-average ratio correction layer; printer model; resolution enhancement; signal processing techniques; Adaptive signal processing; Automatic logic units; Peak to average power ratio; Personal communication networks; Printers; Scanning probe microscopy; Signal processing; Signal processing algorithms; Signal resolution; Vectors;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/TIP.2003.814246

Filename

1212653