Abstract
Error diffusion is a procedure for generating high quality bi-level images from continuous tone images so that both the continuous and halftone images appear similarly when observed from a distance. It is well known that certain objectionable patterning artifacts can occur in error diffused images. Previous approaches for improving the quality of error diffused images include the application of non-standard scanning strategies (e.g., serpentine or Peano scanning), dithering the filter coefficients in error diffusion, dithering the quantizer threshold, incorporating feedback to control the average distance between dots, and designing an optimum error diffusion filter according to some distortion criterion. Here we consider a method for adjusting the error diffusion filter concurrently with the error diffusion process so that an error criterion is minimized. The minimization is performed using the LMS algorithm in adaptive signal processing. Such an algorithm produces better halftone image quality compared to traditional error diffusion with a fixed filter.
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