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Training-based descreening.

Hasib Siddiqui1, Charles A Bouman

  • 1School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907, USA. hsiddiqu@purdue.edu

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|March 16, 2007
PubMed
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This study introduces a novel descreening algorithm combining resolution synthesis-based denoising (RSD) and modified smallest univalue segment assimilating nucleus (SUSAN) filtering to efficiently remove Moiré artifacts from scanned documents. The method also offers deblurring and inverse halftoning capabilities.

Area of Science:

  • Digital image processing
  • Computational imaging

Background:

  • Electrophotographic printers often create Moiré artifacts when printing scanned images from sources like books and magazines.
  • Existing descreening methods may require knowledge of original screening parameters, limiting their practical application.

Purpose of the Study:

  • To develop an efficient descreening algorithm for color scanned documents that effectively solves the Moiré problem.
  • To provide a solution applicable to practical imaging devices such as copiers and multifunction printers.

Main Methods:

  • A novel algorithm combining resolution synthesis-based denoising (RSD) and modified smallest univalue segment assimilating nucleus (SUSAN) filtering.
  • RSD utilizes a trained stochastic image model for pixel classification and filtering.
  • Modified SUSAN filter performs edge-preserving smoothing on RSD output for the final descreened image.

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Main Results:

  • The proposed method successfully suppresses Moiré artifacts without needing prior knowledge of the screening method.
  • The algorithm can be trained for intrinsic sharpening, enabling deblurring of scanned documents.
  • The optimized algorithm can also perform inverse halftoning on images with stochastic error diffusion noise.

Conclusions:

  • This combined RSD and SUSAN approach offers an effective and versatile solution for descreening scanned documents, addressing Moiré artifacts and offering additional image enhancement features.
  • The method's independence from screening parameters and its adaptability make it suitable for diverse practical imaging applications.