A Machine Learning Approach to Design of Aperiodic, Clustered-Dot Halftone Screens via Direct Binary Search

• Published in: IEEE transactions on image processing Vol. 31; pp. 5498 - 5512
• Main Authors: Frank, Tal, Liu, Jiayin, Gat, Shani, Haik, Oren, Mor, Orel Bat, Roth, Itamar, Allebach, Jan P., Yitzhaky, Yitzhak
• Format: Journal Article
• Language: English
• Published: New York IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; aperiodic; clustered-dot halftone texture; color halftoning; Design; direct binary search; Halftone screen; Image color analysis; Image quality; Laser stability; Machine learning; Measurement; Parameters; Presses; print quality; Printers; Printing; radially averaged power spectrum; Satellite broadcasting; Screens

Aperiodic, clustered-dot, halftone patterns have recently become popular for commercial printing of continuous-tone images with laser, electrophotographic presses, because of their inherent stability and resistance to moiré artifacts. Halftone screens designed using the multistage, multipass, cluste...