The recent proliferation of digital binary output devices, such as laser printers and facsimile machines, has brought increased attention to high quality halftone reproduction. A question that often arises in halftone research is how to evaluate the quality of halftone images using a quantitative quality metric. Such metrics would allow objective evaluation, in addition to being independently reproducible. Halftoning introduces unique types of distortions, and to be able to formulate quantitative quality measures for halftones it is first needed to develop visual models that agree with the response of the human visual system to halftone images. However, the problem of developing such models has received scant attention. For the above reasons, the first objective of the proposed research is to investigate how different visual models can predict the quality of halftone images, and then based on these models, formulate quantitative quality metrics. Visual modeling can also be used for the improvement of existing halftone processes, and provide a basis for the development of visual-model-based halftoning algorithms. In the proposed research, visual modeling will be incorporated in the construction of a halftone mask which was developed by the investigator in her Ph.D. thesis. The incorporation of visual modeling will improve the performance of the halftone mask and permit the development of a halftoning algorithm that combines utilization of information about the human visual system and speed, since the mask is completely independent of the image to be halftoned and needs to be constructed only once.
