Demosaicing using variable-size classifiers and proportional weights

Chung-Yen Su, Jen Kang Tseng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Demosaicing is a process of interpolating the missing colors of color filter array. Recently, a quite good demosaicing method using directional filtering and a posteriori decision has been proposed. However, the window size of classifiers in the decision is fixed, which may not be suitable for different kinds of image area. To solve this problem, we present variable-size classifiers in this paper. The size of classifiers is varied according to the roughness measurement of neighbor pixels. In addition, a scheme of proportional weights is proposed to increase the interpolated image quality. Combined with a modified refining step, the proposed method increases a little computational cost but can elevate the peak-signal to noise ratio up to 1.09 dB on average.

Original languageEnglish
Title of host publication2009 IEEE International Conference on Image Processing, ICIP 2009 - Proceedings
PublisherIEEE Computer Society
Pages493-496
Number of pages4
ISBN (Print)9781424456543
DOIs
Publication statusPublished - 2009 Jan 1
Event2009 IEEE International Conference on Image Processing, ICIP 2009 - Cairo, Egypt
Duration: 2009 Nov 72009 Nov 10

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Other

Other2009 IEEE International Conference on Image Processing, ICIP 2009
CountryEgypt
CityCairo
Period09/11/709/11/10

Keywords

  • Color interpolation
  • Demosaicing
  • Edge-adaptive interpolation
  • Proportional weight
  • Variable-size classifier

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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  • Cite this

    Su, C-Y., & Tseng, J. K. (2009). Demosaicing using variable-size classifiers and proportional weights. In 2009 IEEE International Conference on Image Processing, ICIP 2009 - Proceedings (pp. 493-496). [5414343] (Proceedings - International Conference on Image Processing, ICIP). IEEE Computer Society. https://doi.org/10.1109/ICIP.2009.5414343