This paper describes a new approach to adaptive digital halftoning with the least squares model-based (LSMB) 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 LSMB method where the single eye filter is employed uniformly over the image, the model parameters are controlled according to local image characteristics for each pixel. 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 LSMB method.