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Spatially adaptive wavelet thresholding with context modeling for image denoising

Publications associées (54)

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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

Innovations-Based Sampling Over Spatially-Correlated Sensors

Ali H. Sayed

e consider an estimation network of many distributed sensors, where each senor takes a noisy measurement of some unknown parameter. Due to energy limitation, the network selects only a subset of sensors for data fusion as long as the distortion is tolerabl ...

IEEE2007

Nonlinear approximation with redundant multi-component dictionaries

Lorenzo Granai

The problem of efficiently representing and approximating digital data is an open challenge and it is of paramount importance for many applications. This dissertation focuses on the approximation of natural signals as an organized combination of mutually c ...

EPFL2006

Identification of multi-input systems: variance analysis and input design issues

Dominique Bonvin, Alireza Karimi, Ljubisa Miskovic

This paper examines the identification of multi-input systems. Motivated by an experiment design problem (should one excite the various inputs simultaneously or separately), we examine the effect of an additional input on the variance of the estimated coef ...

2006

Directionlets

Vladan Velisavljevic

Efficient representation of geometrical information in images is very important in many image processing areas, including compression, denoising and feature extraction. However, the design of transforms that can capture these geometrical features and repre ...

EPFL2005

Which Wavelet Bases Are the Best for Image Denoising?

Michaël Unser, Thierry Blu, Florian Luisier

We use a comprehensive set of non-redundant orthogonal wavelet transforms and apply a denoising method called SUREshrink in each individual wavelet subband to denoise images corrupted by additive Gaussian white noise. We show that, for various images and a ...

SPIE2005

Rate-distortion optimized geometrical image processing

Rahul Shukla

Since geometrical features, like edges, represent one of the most important perceptual information in an image, efficient exploitation of such geometrical information is a key ingredient of many image processing tasks, including compression, denoising and ...

EPFL2004

Geometrical Image Denoising Using Quadtree Segmentation

Martin Vetterli, Rahul Shukla

We propose a quadtree segmentation based denoising algo- rithm, which attempts to capture the underlying geometrical structure hidden in real images corrupted by random noise. The algorithm is based on the quadtree coding scheme pro- posed in our earlier w ...

2004

Accurate Face Models from Uncalibrated and Ill-Lit Video Sequences

Pascal Fua, Slobodan Ilic, Miodrag Dimitrijevic

In this paper, we propose a face reconstruction technique that produces models that not only look good when texture mapped, but are also metrically accurate. Our method is designed to work with short uncalibrated video or movie sequences, even when the lig ...

2004

Guest Editorial: Wavelets in Medical Imaging

Michaël Unser

I. Introduction Wavelets are the result of collective efforts that recognized common threads between ideas and concepts that had been independently developed and investigated by distinct research communities. They provide a unifying framework for decompos ...

2003