Model-based digital halftoning

The goal of model-based halftoning techniques is to exploit explicit models of the display device and the human visual system (HVS) to maximize the quality of the displayed images. Based on the type of computation involved, halftoning algorithms are broadly classified into three categories: point algorithms (screening or dithering), neighborhood algorithms (error diffusion), and iterative algorithms [least squares and direct binary search (DBS)]. All of these algorithms can incorporate HVS and printer models. However, the best halftone reproductions are obtained by iterative techniques that minimize the (squared) error between the output of the cascade of the printer and visual models in response to the halftone image and the output of the visual model in response to the original continuous-tone image.