HP Labs Technical Reports

Entropy Constrained Halftoning Using Multipath Tree Coding

Wong, Ping Wah

HPL-95-82

Keyword(s):

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 distance between minority pixels in the halftone. A tree coding approach with the ML-algorithm is used for minimizing the distortion criterion and generating a halftone. While this approach generates halftones of high quality, these halftones are not amenable to lossless compression. We introduce an entropy constraint into the cost function of the tree coding algorithm, which optimally trades-off between image quality and compression performance in the output halftones.

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