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Entropy-constrained halftoning using multipath tree coding

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1 Author(s)
Ping Wah Wong ; Hewlett-Packard Co., Palo Alto, CA, USA

We suggest an optimization-based method for halftoning that involves looking ahead 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 (MSE) 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 to generate a halftone. While this approach generates halftones of high quality, these halftones are not very amenable to lossless compression. We introduce an entropy constraint into the cost function of the tree-coding algorithm that optimally trades off between image quality and compression performance in the output halftones

Published in:

IEEE Transactions on Image Processing  (Volume:6 ,  Issue: 11 )