Edge enhancement in clustered-dot dithering

We describe an automated edge enhancement procedure that operates in conjunction with clustered-dot dithering. The goal is not to make weak edges more noticeable, but rather to give the strong edges in the halftoned image a sharper and more natural appearance. Our technique uses a well-known gradient-based edge detection scheme, augmented by pre-smoothing of the input image and post-processing of the resulting edge map. Enhancement is accomplished by means of local adjustments to the dithering threshold values, which result in a tradeoff of grayscale resolution for improved spatial resolution in the vicinity of edges. A rule-based compensation scheme is used to identify and eliminate objectionable pixel patterns caused by the threshold modifications. Experimental results show that our method is successful in improving the appearance of text, line art, and natural scenes rendered by clustered-dot dithering