Adaptive-hierarchical-filtering technique for high-quality magazine image reproduction

This paper proposes a novel adaptive filtering technique to achieve high-quality image enhancement when the image possesses the artifact of moire pattern during the reproduction by different computer peripherals such as color copiers, or scanners plus printers. Commercial magazine images are halftoned images. Unacceptable noises and moire distortion may occur when halftone images are copied (i.e., scanned and printed). In this paper, we analyze the formation of moire patterns in both the frequency and spatial domain. Basically moire noise often appears due to the aliased frequency when a halftone image is scanned. Based on the analysis of the scanned halftone image, we develop an adaptive filter to suppress the moire artifacts and produce the high-quality image reproduction. The adaptive filter consists of modules of anti-aliased filter and image enhance filter: the anti-aliased filter is applied to cancel aliased low frequency components (moire distortion); the image enhance filter is applied to sharpen image edges. It depends on the information provided by an image classification module to decide either the anti-aliased or image enhance module should be applied. The classification module is developed based on a set of pyramid images to determine an edge is either a global true edge (for sharpening enhancement) or a local halftone's micro-structural edge (for moire reduction). Depending on the information from the classification module, the adaptive filter technique then applies the anti-aliased filter to the halftone micro-structured edge or the enhanced filter to the image global edge correctly and efficiently, and therefore both the moire reduction and image enhancement can be achieved simultaneously. Experimental results show the outstanding effectiveness of the presented technique for high-quality magazine image reproduction.