Title :
Image halftoning using multipath tree coding
Author_Institution :
Hewlett-Packard Labs., Palo Alto, CA, USA
Abstract :
We suggest an optimization based method for halftoning that involves looking ahead into the future before a decision for each binary output pixel is made. We first define a mixture distortion criterion that is a combination of a frequency weighted mean square error and a measure depending on the distances between minority pixels in the halftone. A tree coding approach with the ML-algorithm is used for minimizing the distortion criterion and generate a halftone
Keywords :
approximation theory; image coding; maximum likelihood estimation; optimisation; ML-algorithm; binary output pixel; distances; frequency weighted mean square error; halftone; image halftoning; minority pixels; mixture distortion criterion; multipath tree coding; optimization based method; Distortion measurement; Humans; Image coding; Laboratories; Mean square error methods; Milling machines; Minimization methods; Optimization methods; Pixel; Viterbi algorithm;
Conference_Titel :
Image Processing, 1994. Proceedings. ICIP-94., IEEE International Conference
Conference_Location :
Austin, TX
Print_ISBN :
0-8186-6952-7
DOI :
10.1109/ICIP.1994.413525
