Nonlinear detail enhancement of error-diffused images

Error diffusion distributes the quantization error over the local neighborhood in such a way that the local mean of the halftoned image is adjusted to the local mean of the original image. This works fairly well in homogeneous portions of the image. But along edges and in areas with fine texture and details, spreading the error out over some pixels inevitably blurs the image locally and obscures details. In this paper, a variation of the standard error diffusion algorithm is proposed using a nonlinear filter for feature extraction. With this filter the error diffusion process can be adapted to the local image characteristics in such a way that the quantization error is not diffused across edges. This leads to sharper halftoned images with more detail information. It also increases the local image contrast which results in an overall perceptually more pleasing rendering of the halftoned image.