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Blind optimization of algorithm parameters for signal denoising by Monte-Carlo sure

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Nonideal sampling and regularized interpolation of noisy data

Sathish Ramani

Conventional sampling (Shannon's sampling formulation and its approximation-theoretic counterparts) and interpolation theories provide effective solutions to the problem of reconstructing a signal from its samples, but they are primarily restricted to the ...

EPFL2009

SURE-Based Non-Local Means

Dimitri Nestor Alice Van De Ville, Michel Kocher

Non-local means (NLM) provides a powerful framework for denoising. However, there are a few parameters of the algorithm-most notably, the width of the smoothing kernel-that are data-dependent and difficult to tune. Here, we propose to use Stein's unbiased ...

Institute of Electrical and Electronics Engineers2009

Coding Along Hermite Polynomials for Gaussian Noise Channels

This paper shows that the capacity achieving input distribution for a fading Gaussian broadcast channel is not Gaussian in general. The construction of non-Gaussian distributions that strictly outperform Gaussian ones, for certain characterized fading dist ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2009

Phase-step estimation in interferometry via an unscented Kalman filter

Pramod Rastogi, Abhijit Patil

We present an unscented Kalman filter to identify the phase step imparted to a piezoelectric transducer in phase shifting interferometry in the presence of Gaussian noise. The advantage of the proposed algorithm lies in its ability to determine the phase s ...

2009

Blind Optimization of Algorithm Parameters for Signal Denoising by Monte-Carlo SURE

Michaël Unser, Thierry Blu, Sathish Ramani

We consider the problem of optimizing the parameters of an arbitrary denoising algorithm by minimizing Stein's Unbiased Risk Estimate (SURE) which provides a means of assessing the true mean-squared-error (MSE) purely from the measured data assuming that i ...

IEEE2008

Monte-Carlo SURE: A Black-Box Optimization of Regularization Parameters for General Denoising Algorithms

Michaël Unser, Thierry Blu, Sathish Ramani

We consider the problem of optimizing the parameters of a given denoising algorithm for restoration of a signal corrupted by white Gaussian noise. To achieve this, we propose to minimize Stein's unbiased risk estimate (SURE) which provides a means of asses ...

IEEE2008

SURE-Let Multichannel Image Denoising: Undecimated Wavelet Thresholding

Thierry Blu, Florian Luisier

We propose an extension of the recently devised SURE-LET grayscale denoising approach for multichannel images. Assuming additive Gaussian white noise, the unknown linear parameters of a transform-domain pointwise multichannel thresholding are globally opti ...

IEEE2008

SURE-LET multichannel image denoising: Undecimated wavelet thresholding

Thierry Blu, Florian Luisier

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2008

SURE-LET interscale-intercolor wavelet thresholding for color image denoising - art. no. 67011H

Thierry Blu, Florian Luisier

We propose a new orthonormal wavelet thresholding algorithm for denoising color images that are assumed to be corrupted by additive Gaussian white noise of known intercolor covariance matrix. The proposed wavelet denoiser consists of a linear expansion of ...

Spie-Int Soc Optical Engineering, Po Box 10, Bellingham, Wa 98227-0010 Usa2007

SURE-LET Interscale-Intercolor Wavelet Thresholding for Color Image Denoising

Thierry Blu, Florian Luisier

SPIE2007