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Proceedings Paper

Descreening using segmentation-based adaptive filtering
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Paper Abstract

Ordered halftone patterns in the original document interact with the periodic sampling of the scanner, producing objectionable moir´e patterns. These are exacerbated when the copy is reprinted with an ordered halftone pattern. A simple, small low-pass filter can be used to descreen the image and to correct the majority of moir´e artifacts. Unfortunately, low-pass filtering affects detail as well, blurring it even further. Adaptive nonlinear filtering based on image features such as the magnitude and the direction of image gradient can also be used. However, non careful tuning of such filters could either cause damage to small details while descreeing the halftone areas, or result in less descreening while sharpening small details. In this paper, we present a new segmentation-based descreening technique. Scanned images are segmented into text, images and halftone classes using a multiresolution classification of edge features. The segmentation results guide a nonlinear, adaptive filter to favor sharpening or blurring of image pixels belonging to different classes. Our experimental results show the ability of the non-linear, segmentation driven filter of successfully descreening halftone areas while sharpening small size text contents.

Paper Details

Date Published: 3 February 2011
PDF: 8 pages
Proc. SPIE 7870, Image Processing: Algorithms and Systems IX, 78700E (3 February 2011); doi: 10.1117/12.872516
Show Author Affiliations
Mohamed N. Ahmed, Lexmark International, Inc. (United States)
Ahmed H. Eid, Lexmark International, Inc. (United States)


Published in SPIE Proceedings Vol. 7870:
Image Processing: Algorithms and Systems IX
Jaakko T. Astola; Karen O. Egiazarian, Editor(s)

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