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» Complexity-Regularized Image Denoising
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TSP
2010
13 years 2 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
ICIP
2004
IEEE
14 years 9 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
11 years 10 months 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»
13 years 6 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»
13 years 2 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...