Recent advances in digital halftoning and inverse halftoning methods

Halftoning is the rendition of continuous-tone pictures on displays, paper or other media that are capable of producing only two levels. In digital halftoning, we perform the gray scale to bilevel conversion digitally using software or hardware. In the last three decades, several algorithms have evolved for halftoning. Examples of algorithms include ordered dither, error diffusion, blue noise masks, green noise halftoning, direct binary search (DBS), and dot diffusion. In this paper, we first review some of the algorithms which have a direct bearing on our paper and then describe some of the more recent advances in the field. The dot-diffusion method for digital halftoning has the advantage of pixel-level parallelism unlike the error-diffusion method, which is a popular halftoning method. However, the image quality offered by error diffusion is still regarded as superior to most of the other known methods. We first review error diffusion and dot diffusion, and describe a recent method to improve the image quality of the dot-diffusion algorithm which takes advantage of the Human Visual System (HVS) function. Then, we discuss the inverse halftoning problem.