An effective aggregation function for image denoising based on low rank matrix completion

Dongni Zhang, Sung Ho Lee, Hoon Kim, Jong Woo Han, Sung Jea Ko

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

1 Citation (Scopus)

Abstract

In this paper, an aggregation function is proposed to improve the performance of the conventional denoising method based on low rank matrix completion. Since this method determines the denoised value of each pixel by averaging the corresponding pixels in the denoised image patches, the performance can be improved by a reasonable aggregation function. The proposed aggregation function exploits the intensity similarity and geometry closeness of the denoised patches, to reduce the unwanted artifacts in the synthesized denoised image. Experimental results show that the proposed method achieves substantial PSNR improvement as compared with the conventional denoising algorithm.

Original languageEnglish
Title of host publicationProceedings - 2011 4th International Symposium on Knowledge Acquisition and Modeling, KAM 2011
Pages219-221
Number of pages3
DOIs
Publication statusPublished - 2011
Event2011 4th International Symposium on Knowledge Acquisition and Modeling, KAM 2011 - Sanya, China
Duration: 2011 Oct 82011 Oct 9

Publication series

NameProceedings - 2011 4th International Symposium on Knowledge Acquisition and Modeling, KAM 2011

Other

Other2011 4th International Symposium on Knowledge Acquisition and Modeling, KAM 2011
CountryChina
CitySanya
Period11/10/811/10/9

Keywords

  • Aggregation function
  • low rank matrix completion
  • patch-based image denoising

ASJC Scopus subject areas

  • Computer Science Applications
  • Modelling and Simulation

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  • Cite this

    Zhang, D., Lee, S. H., Kim, H., Han, J. W., & Ko, S. J. (2011). An effective aggregation function for image denoising based on low rank matrix completion. In Proceedings - 2011 4th International Symposium on Knowledge Acquisition and Modeling, KAM 2011 (pp. 219-221). [6137619] (Proceedings - 2011 4th International Symposium on Knowledge Acquisition and Modeling, KAM 2011). https://doi.org/10.1109/KAM.2011.65