Publications by Florian Luisier

Image Denoising in Mixed Poisson-Gaussian Noise

Michaël Unser, Thierry Blu, Florian Luisier

We propose a general methodology (PURE-LET) to design and optimize a wide class of transform-domain thresholding algorithms for denoising images corrupted by mixed Poisson-Gaussian noise. We express the denoising process as a linear expansion of thresholds ...

Institute of Electrical and Electronics Engineers2011

Fast Interscale Wavelet Denoising of Poisson-Corrupted Images

Michaël Unser, Thierry Blu, Cédric René Jean Vonesch, Florian Luisier

We present a fast algorithm for image restoration in the presence of Poisson noise. Our approach is based on (1) the minimization of an unbiased estimate of the MSE for Poisson noise, (2) a linear parametrization of the denoising process and (3) the preser ...

Elsevier2010

SURE-LET for Orthonormal Wavelet-Domain Video Denoising

Michaël Unser, Thierry Blu, Florian Luisier

We propose an efficient orthonormal wavelet-domain video denoising algorithm based on an appropriate integration of motion compensation into an adapted version of our recently devised Stein's unbiased risk estimator-linear expansion of thresholds (SURE-LET ...

IEEE2010

Undecimated Haar Thresholding For Poisson Intensity Estimation

Michaël Unser, Thierry Blu, Florian Luisier

We propose a novel algorithm for denoising Poisson-corrupted images, that performs a signal-adaptive thresholding of the undecimated Haar wavelet coefficients. A Poisson's unbiased MSE estimate is devised and adapted to arbitrary transform-domain pointwise ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2010

The SURE-LET approach to image denoising

Florian Luisier

Denoising is an essential step prior to any higher-level image-processing tasks such as segmentation or object tracking, because the undesirable corruption by noise is inherent to any physical acquisition device. When the measurements are performed by phot ...

EPFL2010

Fast Haar-Wavelet Denoising Of Multidimensional Fluorescence Microscopy Data

Michaël Unser, Thierry Blu, Cédric René Jean Vonesch, Florian Luisier

We propose a novel denoising algorithm to reduce the Poisson noise that is typically dominant in fluorescence microscopy data. To process large datasets at a low computational cost, we use the unnormalized Haar wavelet transform. Thanks to some of its appe ...

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

Multiframe SURE-LET denoising of timelapse fluorescence microscopy images

Michaël Unser, Thierry Blu, Saskia Joëlle Delpretti Anex, Florian Luisier, Sathish Ramani

Due to the random nature of photon emission and the various internal noise sources of the detectors, real timelapse fluorescence microscopy images are usually modeled as the sum of a Poisson process plus some Gaussian white noise. In this paper, we propose ...

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

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 ...

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

SURE-LET Multichannel Image Denoising: Interscale Orthonormal Wavelet Thresholding

Thierry Blu, Florian Luisier

We propose a vector/matrix extension of our denoising algorithm initially developed for grayscale images, in order to efficiently process multichannel (e.g., color) images. This work follows our recently published SURE-LET approach where the denoising algo ...

Institute of Electrical and Electronics Engineers2008

Image denoising by pointwise thresholding of the undecimated wavelet coefficients: A global sure optimum

Thierry Blu, Florian Luisier

We devise a new undecimated wavelet thresholding for denoising images corrupted by additive Gaussian white noise. The first key point of our approach is the use of a linearly parameterized pointwise thresholding function. The second key point consists in o ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2007