Halftoning Algorithm Using Pull-Based Error Diffusion Technique

Despite several improvements in the field of digital halftoning, there is still a scope of improvement. Halftoning is widely applied for applications like printing, efficient transmission, and storage, etc. Halftoning process reduces 256 levels of a grayscale image to just 2 levels. Three major categories of halftoning are (1) Dithering, (2) Error Diffusion, and (3) Iterative algorithms. A concern always remains regarding the visual perception of an image’s halftone output and for obtaining a good visual perception, we have proposed an error diffusion algorithm that applies pulling technique. The perception of output image generated by our algorithm is similar to the input. The SSIM (structure similarity index map), PSNR (peak signal-to-noise ratio), RMSE (root mean squared error), and MSE (mean squared error), of the output image are 0.1426, 7.2672, 110.4531, and 1.2200e+04, respectively.