Image denoising by arithmetic means based on similarity

Yutaka Takagi, Masaaki Ikehara

    研究成果: Conference contribution

    抄録

    In this paper, we propose a Non-Local Means algorithm-based denoising method. In conventional NLM, the weighting functions are acquired based on the similarity between target patch and its neighboring patches and then Gaussian-range kernel is calculated based on the similarity. Then, target patch is replaced by weighted means value of neighboring patches. In comparison, our method extracts similar patches by thresholding and only calculates simple arithmetic average. The method does not only outperform the conventional NLM but also implement with less computation. Finally, we compare the proposed and the conventional NLM, and validate the advantage.

    本文言語English
    ホスト出版物のタイトル2015 10th International Conference on Information, Communications and Signal Processing, ICICS 2015
    出版社Institute of Electrical and Electronics Engineers Inc.
    ISBN(電子版)9781467372183
    DOI
    出版ステータスPublished - 2016 4 26
    イベント10th International Conference on Information, Communications and Signal Processing, ICICS 2015 - Singapore, Singapore
    継続期間: 2015 12 22015 12 4

    Other

    Other10th International Conference on Information, Communications and Signal Processing, ICICS 2015
    CountrySingapore
    CitySingapore
    Period15/12/215/12/4

    ASJC Scopus subject areas

    • Computer Networks and Communications
    • Information Systems
    • Signal Processing

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