Edge-Enhanced Error Diffusion Halftoning using Human Visual Properties

Digital halftoning is the technique to obtain a bilevel-toned image from continuous-toned image. Among halftoning methods, the error diffusion method gives better subjective quality than other halftoning ones. But it also makes edges of objects blurred. To overcome the defect, we proposes the modified error diffusion to enhance the edges using the property that human vision perceives the local average luminance and doesn´t perceive a little variation of the spatial information. The proposed method computes a local activity measure, which is the difference between a pixel luminance and the average of its 3times3 neighborhood pixels´ luminance weighted according to the spatial positioning. The system also uses information of edge enhancement (IEE), which is computed from the normalized spatial activity measure multiplied by the average luminance. The IEE is added to the quantizer´s input pixel and feeds into the halftoning quantizer. The quantizer produces the halftone image having the enhanced edge. The computer experimental results show that the proposed method produces clearer bilevel-toned images than conventional methods and the edge of objects is preserved well. Also the performance of the proposed method is improved, compared with that of the conventional method by measuring the edge correlation and the local average accordance at some ranges of viewing distance