Adaptive model-based digital halftoning incorporating image enhancement

摘要

This paper describes a new approach to adaptive digital halftoning with the least-squares model-based method. A framework is presented for the adaptive control of smoothness and sharpness of the halftone patterns according to local image characteristics. The proposed method employs explicit, quantitative models of the human visual system represented as 2-D linear filters (eye filters). In contrast with the standard least-squares model-based method where a single eye filter is employed uniformly over the image, the model parameters are controlled according to local image characteristics for each pixel, and therefore, different eye filters are assigned to the pixels. The halftone image is computed with a simple heuristic algorithm based on the error criterion in terms of the eye filters. Because of the adaptive selection of eye filters for the pixels, image enhancement is incorporated into the halftoning process. Effectiveness of the proposed approach is demonstrated through experiments using real data compared with the error-diffusion algorithm and the standard least-squares model-based method.