Optimal error diffusion for digital halftoning using an optical neural network

A novel technique for digital image halftoning is proposed based on a symmetric error diffusion algorithm and an optical realization of a neural network. Using this approach, all pixel quantization decisions are computed in parallel and therefore the diffusion filter need not be causal. Visual artifacts resulting from the causality of the diffusion filter are reduced and therefore halftoned image quality is improved. Also, the inherent parallelism associated with optical processing can reduce the computational requirements while decreasing the total convergence time of the halftoning process