SURE-LET Poisson Denoising with Multiple Directional LOTs

• CHEN Zhiyu

  Graduate School of Science and Technology, Niigata University

• MURAMATSU Shogo

  Dept. of Electrical and Electronic Engineering, Niigata University

抄録

This paper proposes a Poisson denoising method with a union of directional lapped orthogonal transforms (DirLOTs). DirLOTs are 2-D non-separable lapped orthogonal transforms with directional characteristics under the fixed-critically-subsampling, overlapping, orthonormal, symmetric, real-valued and compact-support property. In this work, DirLOTs are used to generate symmetric orthogonal discrete wavelet transforms and then a redundant dictionary as a union of unitary transforms. The multiple directional property is suitable for representing natural images which contain diagonal textures and edges. Multiple DirLOTs can overcome a disadvantage of separable wavelets in representing diagonal components. In addition to this feature, multiple DirLOTs make transform-based denoising performance better through the redundant representation. Experimental results show that the combination of the variance stabilizing transformation (VST), Stein's unbiased risk estimator-linear expansion of threshold (SURE-LET) approach and multiple DirLOTs is able to significantly improve the denoising performance.

収録刊行物

• IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

  IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E98.A (8), 1820-1828, 2015

  一般社団法人 電子情報通信学会

キーワード

• Poisson noise
• multiple DirLOTs
• wavelet shrinkage
• anscombe transform
• SURE-LET

詳細情報

• CRID: 1390001206310095744
• NII論文ID: 130005089911
• DOI: 10.1587/transfun.e98.a.1820
• ISSN: 17451337
• ISSN: 09168508
• Web Site: https://www.jstage.jst.go.jp/article/transfun/E98.A/8/E98.A_1820/_pdf
• 本文言語コード: en
• データソース種別:
  • JaLC
  • Crossref
  • CiNii Articles
  • KAKEN
• 抄録ライセンスフラグ: 使用不可