Patch based image denoising using the finite ridgelet transform for less artifacts

Yun Xia Liu, Ngai Fong Law, Wan Chi Siu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

15 Citations (Scopus)


Patch based denoising methods have proved to lead to state-of-the-art results. However, in contrast with intensive pursuing of higher peak signal to noise ratio (PSNR), less attention is paid to visual quality improvement of denoised images. In this paper, we first compare the denoising performance in edge and smooth regions. Results reveal that edge regions are the main source for potential performance improvement. This motivates us to investigate the use of the finite ridgelet transform as a local transform for better preservation of directional singularities. A two stage denoising algorithm is then proposed to improve the representation of detail structures. Experimental results in denoising images which only contain white noise show that the proposed algorithm consistently outperforms other methods in terms of PSNR and Structural SIMilarity index. Denoised images by the proposed method also demonstrate good visual quality with the least artifacts and fake structures in experiments on natural images.
Original languageEnglish
Pages (from-to)1006-1017
Number of pages12
JournalJournal of Visual Communication and Image Representation
Issue number5
Publication statusPublished - 1 Jan 2014


  • Artifact
  • Finite ridgelet transform
  • Image denoising
  • Shrinkage
  • Visual quality

ASJC Scopus subject areas

  • Signal Processing
  • Media Technology
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering


Dive into the research topics of 'Patch based image denoising using the finite ridgelet transform for less artifacts'. Together they form a unique fingerprint.

Cite this