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

    2 Citations (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
    Country/TerritoryChina
    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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