AM/FM halftoning: improved cost function and training framework

Abstract

FM halftoning generates good tone rendition but it is not appropriate for electrophotographic (EP) printers due to the inherent instability of the EP process. Although AM halftoning yields stable dots, it is susceptible to moire and contouring artifacts. To combine the strengths of AM and FM halftoning, the AM/FM halftoning algorithm exploits each advantage of AM and FM halftoning. The resulting halftone textures have green noise spectral characteristics. In this paper, we present an improved training procedure for the AM/FM halftoning algorithm. Since most of the green noise energy is concentrated in the middle frequencies, the tone dependent error diffusion (TDED) parameters (weights and thresholds) are optimized using a new cost function with normalization to distribute the cost evenly over all frequencies. With the new cost function, we can obtain image quality that is very close to the direct binary search (DBS) search-based dispersed-dot halftoning algorithm. The cost function for training the AM part is also modified by penalizing variation in measured tone value across the multiple printer conditions for each combination of dot size and dot density.