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
APA
Chicago
ICMJE
MLA
NLM
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