A nonlinear adaptive regression process for noise corrupt images

Nan Jiang, Changchun Li, Jennie Si, Glen P. Abonsleman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Most existing nonlinear regression filtering techniques for image denoising are claimed to be edge preserving without considering the pixel position information. This will cause speckling effects on the denoised image and inconsistent smoothing in the vicinity of texture-rich areas. This paper proposes a novel denoising method to address this problem. The proposed method removes the low to intermediate noise using edge-preserving range filtering, thereby removing short, false edges. The updated edge map is used for subsequent filtering in which pixel intensities are smoothed according to their minimum distance to the closest edge point. This procedure is carried out in an iterative scheme until the edge map stabilizes. We compare existing denoising algorithms with the proposed method. Experimental results validate the effectiveness and efficiency of the proposed method.

Original languageEnglish (US)
Title of host publication2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Pages901-904
Number of pages4
DOIs
StatePublished - Sep 16 2008
Event2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP - Las Vegas, NV, United States
Duration: Mar 31 2008Apr 4 2008

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
CountryUnited States
CityLas Vegas, NV
Period3/31/084/4/08

Keywords

  • Bilateral filtering
  • Image denoising
  • Local data adaptive
  • Partial differential function
  • Wavelet shrinkage

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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  • Cite this

    Jiang, N., Li, C., Si, J., & Abonsleman, G. P. (2008). A nonlinear adaptive regression process for noise corrupt images. In 2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP (pp. 901-904). [4517756] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.2008.4517756