Evaluating the fidelity of a partitioned digital image halftoning algorithm

David A. Nash; Jean R. S. Blair; Tommy D. Wagner; Eugene K. Ressler Jr.; Barry L. Shoop

doi:10.1117/12.438266

28 August 2001 Evaluating the fidelity of a partitioned digital image halftoning algorithm

David A. Nash, Jean R. S. Blair, Tommy D. Wagner, Eugene K. Ressler Jr., Barry L. Shoop

Proceedings Volume 4388, Visual Information Processing X; (2001) https://doi.org/10.1117/12.438266
Event: Aerospace/Defense Sensing, Simulation, and Controls, 2001, Orlando, FL, United States

Abstract

In previous work we developed a partitioning strategy called constrained framing, which was used to implement an error diffusion neural network for digital image halftoning. The partitioning approach made it possible to implement the original technique in a distributed, parallel fashion. The resulting halftoned images were visually indistinguishable from the non-partitioned approach. Ulichney's halftone metrics of radially averaged power spectra and anisotropy also did not show noticeable differences between the two techniques. Even an intensive application of the power spectra metric (averaging 1000 halftoned images instead of 10) revealed the need for some additional metrics of quality. Taking advantage of a priori knowledge of the partition scheme's geometry, we develop a protocol for evaluating the subtle differences between halftoned images produced using the constrained framing algorithm and the non-tiled halftone. An observed relationship between the new metric and input image grayscale magnitude suggests the existence of normative values which may be used to examine the performance of other halftone algorithms which are applied in a similar segmented fashion.

Citation Download Citation

David A. Nash, Jean R. S. Blair, Tommy D. Wagner, Eugene K. Ressler Jr., and Barry L. Shoop "Evaluating the fidelity of a partitioned digital image halftoning algorithm", Proc. SPIE 4388, Visual Information Processing X, (28 August 2001); https://doi.org/10.1117/12.438266

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