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 publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Pages901-904
Number of pages4
DOIs
StatePublished - 2008
Event2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP - Las Vegas, NV, United States
Duration: Mar 31 2008Apr 4 2008

Other

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

Fingerprint

regression analysis
Pixels
Image denoising
preserving
Textures
pixels
smoothing
textures
causes

Keywords

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

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Signal Processing
  • Acoustics and Ultrasonics

Cite this

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

A nonlinear adaptive regression process for noise corrupt images. / Jiang, Nan; Li, Changchun; Si, Jennie; Abonsleman, Glen P.

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. 2008. p. 901-904 4517756.

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

Jiang, N, Li, C, Si, J & Abonsleman, GP 2008, A nonlinear adaptive regression process for noise corrupt images. in ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings., 4517756, pp. 901-904, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP, Las Vegas, NV, United States, 3/31/08. https://doi.org/10.1109/ICASSP.2008.4517756
Jiang N, Li C, Si J, Abonsleman GP. A nonlinear adaptive regression process for noise corrupt images. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. 2008. p. 901-904. 4517756 https://doi.org/10.1109/ICASSP.2008.4517756
Jiang, Nan ; Li, Changchun ; Si, Jennie ; Abonsleman, Glen P. / A nonlinear adaptive regression process for noise corrupt images. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. 2008. pp. 901-904
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