External patch prior guided internal clustering for image denoising

Fei Chen, Lei Zhang, Huimin Yu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

88 Citations (Scopus)

Abstract

Natural image modeling plays a key role in many vision problems such as image denoising. Image priors are widely used to regularize the denoising process, which is an illposed inverse problem. One category of denoising methods exploit the priors (e.g., TV, sparsity) learned from external clean images to reconstruct the given noisy image, while another category of methods exploit the internal prior (e.g., self-similarity) to reconstruct the latent image. Though the internal prior based methods have achieved impressive denoising results, the improvement of visual quality will become very difficult with the increase of noise level. In this paper, we propose to exploit image external patch prior and internal self-similarity prior jointly, and develop an external patch prior guided internal clustering algorithm for image denoising. It is known that natural image patches form multiple subspaces. By utilizing Gaussian mixture models (GMMs) learning, image similar patches can be clustered and the subspaces can be learned. The learned GMMs from clean images are then used to guide the clustering of noisypatches of the input noisy images, followed by a low-rank approximation process to estimate the latent subspace for image recovery. Numerical experiments show that the proposed method outperforms many state-of-the-art denoising algorithms such as BM3D and WNNM.
Original languageEnglish
Title of host publication2015 International Conference on Computer Vision, ICCV 2015
PublisherIEEE
Pages603-611
Number of pages9
Volume2015 International Conference on Computer Vision, ICCV 2015
ISBN (Electronic)9781467383912
DOIs
Publication statusPublished - 17 Feb 2015
Event15th IEEE International Conference on Computer Vision, ICCV 2015 - Santiago, Chile
Duration: 11 Dec 201518 Dec 2015

Conference

Conference15th IEEE International Conference on Computer Vision, ICCV 2015
Country/TerritoryChile
CitySantiago
Period11/12/1518/12/15

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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