Frequency-channel-based visual models as quantitative quality measures in halftoning

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, could be incorporated in halftoning algorithms, in addition to being independently reproducible. Given that halftoning introduces unique types of distortions and the display medium (a hardcopy device) is different than that of conventional image processing applications (a CRT display), it becomes necessary to develop visual models specifically for halftoning applications. In this paper, frequency-domain visual models are investigated as to their suitability for the formulation of quantitative quality metrics specifically for halftoning applications. Two types of frequency-domain models are investigated: models that utilize a simple contrast-sensitivity function and models that utilize multiple independent narrowband channels. The quantitative quality metric for both types of models is formulated as a weighted frequency domain error. Since the ultimate judges of image quality are human viewers, the success of the quantitative measures is assessed by comparing their results with the results of a psychovisual test performed on halftone images.