Rapid and Accurate Local Gaussian Noise Removal

Shogo Seta, Yusuke Nakahara, Takuro Yamaguchi, Masaaki Ikehara

研究成果: Conference contribution

抄録

In this paper, we propose a rapid and high-accuracy Gaussian noise removal method by applying the learning linear filter used in RAISR for super-resolution. Our algorithm is a rapid local method, yet produces comparable results to the accuracy of the non-local method known for its high accuracy. The novelty of this paper is that the same processing as super-resolution is incorporated into denoising. The conventional local processing includes smoothing processing, and has a problem that high-frequency components of an original signal are lost while reducing the noise. In order to solve the problem, this method incorporates a super-resolution method that compensates for high-frequency components as post-processing. The super-resolution method utilizes a process that applies a learning linear filter according to the feature of patches in RAISR. Because the proposed method consists of local precessing, its operation is rapid compared to non local processing like BM3D.

本文言語English
ホスト出版物のタイトル2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 - Proceedings
出版社Institute of Electrical and Electronics Engineers Inc.
ページ1222-1225
ページ数4
ISBN(電子版)9789881476883
出版ステータスPublished - 2020 12 7
イベント2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 - Virtual, Auckland, New Zealand
継続期間: 2020 12 72020 12 10

出版物シリーズ

名前2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 - Proceedings

Conference

Conference2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020
国/地域New Zealand
CityVirtual, Auckland
Period20/12/720/12/10

ASJC Scopus subject areas

  • 人工知能
  • コンピュータ ネットワークおよび通信
  • コンピュータ ビジョンおよびパターン認識
  • ハードウェアとアーキテクチャ
  • 信号処理
  • 決定科学(その他)
  • 器械工学

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