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» Complexity-Regularized Image Denoising
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71
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TSP
2010
14 years 4 months ago
Closed-form MMSE estimation for signal denoising under sparse representation modeling over a unitary dictionary
This paper deals with the Bayesian signal denoising problem, assuming a prior based on a sparse representation modeling over a unitary dictionary. It is well known that the maximum...
Matan Protter, Irad Yavneh, Michael Elad
93
Voted
ICIP
2004
IEEE
15 years 11 months ago
Least-squares interband denoising of color and multispectral images
This paper exploits the interband correlations of color and multispectral images for wavelet-based denoising. For this, a multispectral extension of the linear minimum mean square...
Paul Scheunders, Jef Driesen
CVPR
2012
IEEE
13 years 3 days ago
Light field denoising, light field superresolution and stereo camera based refocussing using a GMM light field patch prior
With the recent availability of commercial light field cameras, we can foresee a future in which light field signals will be as common place as images. Hence, there is an immine...
Kaushik Mitra, Ashok Veeraraghavan
TIP
2008
213views more  TIP 2008»
14 years 8 months ago
Deblurring Using Regularized Locally Adaptive Kernel Regression
Kernel regression is an effective tool for a variety of image processing tasks such as denoising and interpolation [1]. In this paper, we extend the use of kernel regression for de...
Hiroyuki Takeda, Sina Farsiu, Peyman Milanfar
TIP
2010
154views more  TIP 2010»
14 years 4 months ago
Efficient Fourier-Wavelet Super-Resolution
Super-resolution (SR) is the process of combining multiple aliased low-quality images to produce a high-resolution high-quality image. Aside from registration and fusion of low-res...
M. Dirk Robinson, Cynthia A. Toth, Joseph Y. Lo, S...