DocumentCode :
2633849
Title :
Some methods for practical halftoning on the CNN universal machine
Author :
Crounse, Kenneth R. ; Roska, Tamás ; Chua, Leon O.
Author_Institution :
Lab. of Nonlinear Electron., California Univ., Berkeley, CA, USA
fYear :
1998
fDate :
14-17 Apr 1998
Firstpage :
337
Lastpage :
342
Abstract :
This paper explores two issues which are relevant in practical halftoning situations on the CNN universal machine: block processing of large images with small CNN arrays, and the use of no larger than 3×3 templates. It is shown that block processing can be performed without noticeable boundary artifacts by careful selection of boundary cell values. In this example, a standard 3×3 halftoning template is used; higher quality halftones can be obtained only by using larger templates. A CNNUM algorithm is introduced which uses only a 3×3 template but emulates a much larger effective template through an iterative procedure. The method is to discretize the CNN transient in time and then implement the spatial correlations at each time step with a CNN transient. An A-B-template pair was designed for a single CNN transient to approximate a very simple linear filter model of the human visual system. The resulting discrete-time system was analyzed. The iterative procedure is demonstrated to produce a visually pleasing halftone
Keywords :
cellular neural nets; discrete time systems; image processing; iterative methods; optical correlation; parallel algorithms; CNN universal machine; CNNUM algorithm; boundary cell values; cellular neural network; discrete-time system; halftoning; human visual system; image block processing; iterative method; linear filter model; spatial correlations; templates; Automation; Cellular neural networks; Gray-scale; Humans; Image processing; Iterative algorithms; Laboratories; Nonlinear filters; Turing machines; Visual system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cellular Neural Networks and Their Applications Proceedings, 1998 Fifth IEEE International Workshop on
Conference_Location :
London
Print_ISBN :
0-7803-4867-2
Type :
conf
DOI :
10.1109/CNNA.1998.685397
Filename :
685397
Link To Document :
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