Quality Assessment for Halftone Images

Abstract: Halftones are reproductions of images created through the process of halftoning. The goal of halftones is to create a replica of an image which, at a distance, looks nearly identical to the original. Several different methods for producing these halftones are available, three of which are error diffusion, DBS and IMCDP. To check whether a halftone would be perceived as of high quality there are two options: Subjective image quality assessments (IQA’s) and objective image quality (IQ) measurements. As subjective IQA’s often take too much time and resources, objective IQ measurements are preferred. But as there is no standard for which metric should be used when working with halftones, this brings the question of which one to use. For this project both online and on-location subjective testing was performed where observers were tasked with ranking halftoned images based on perceived image quality, the images themselves being chosen specifically to show a wide range of characteristics such as brightness and level of detail. The results of these tests were compiled and then compared to that of eight different objective metrics, the list of which is the following: MSE, PSNR, S-CIELAB, SSIM, BlurMetric, BRISQUE, NIQE and PIQE. The subjective and objective results were compared using Z-scores and showed that SSIM and NIQE were the objective metrics which most closely resembled the subjective results. The online and on-location subjective tests differed greatly for dark colour halftones and colour halftones containing smooth transitions, with a smaller variation for the other categories chosen. What did not change was the clear preference for DBS by both the observers and the objective IQ metrics, making it the better of the three methods tested.