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Image denoising by adaptive kernel regression

Publication ,  Journal Article
Takeda, H; Farsiu, S; Milanfar, P
Published in: Conference Record - Asilomar Conference on Signals, Systems and Computers
December 1, 2005

This paper introduces an extremely robust adaptive denoising filter in the spatial domain. The filter is based on non-parametric statistical estimation methods, and in particular generalizes an adaptive method proposed earlier by Fukunaga [1]. To denoise a pixel, the proposed filter computes a locally adaptive set of weights and window sizes, which can be proven to be optimal in the context of non-parametric estimation using kernels. While we do not report analytical results on the statistical efficiency of the proposed method in this paper, we will discuss its derivation, and experimentally demonstrate its effectiveness against competing techniques at low SNR and on real noisy data. © 2005 IEEE.

Duke Scholars

Published In

Conference Record - Asilomar Conference on Signals, Systems and Computers

ISSN

1058-6393

Publication Date

December 1, 2005

Volume

2005

Start / End Page

1660 / 1665
 

Citation

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Takeda, H., Farsiu, S., & Milanfar, P. (2005). Image denoising by adaptive kernel regression. Conference Record - Asilomar Conference on Signals, Systems and Computers, 2005, 1660–1665.
Takeda, H., S. Farsiu, and P. Milanfar. “Image denoising by adaptive kernel regression.” Conference Record - Asilomar Conference on Signals, Systems and Computers 2005 (December 1, 2005): 1660–65.
Takeda H, Farsiu S, Milanfar P. Image denoising by adaptive kernel regression. Conference Record - Asilomar Conference on Signals, Systems and Computers. 2005 Dec 1;2005:1660–5.
Takeda, H., et al. “Image denoising by adaptive kernel regression.” Conference Record - Asilomar Conference on Signals, Systems and Computers, vol. 2005, Dec. 2005, pp. 1660–65.
Takeda H, Farsiu S, Milanfar P. Image denoising by adaptive kernel regression. Conference Record - Asilomar Conference on Signals, Systems and Computers. 2005 Dec 1;2005:1660–1665.

Published In

Conference Record - Asilomar Conference on Signals, Systems and Computers

ISSN

1058-6393

Publication Date

December 1, 2005

Volume

2005

Start / End Page

1660 / 1665