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- Minh N. Do, Martin Vetterli
- IEEE Transactions on Image Processing
- 2005

The limitations of commonly used separable extensions of one-dimensional transforms, such as the Fourier and wavelet transforms, in capturing the geometry of image edges are well known. In this paper, we pursue a "true" two-dimensional transform that can capture the intrinsic geometrical structure that is key in visual information. The main challenge in… (More)

- S. Grace Chang, Bin Yu, Martin Vetterli
- IEEE Trans. Image Processing
- 2000

The first part of this paper proposes an adaptive, data-driven threshold for image denoising via wavelet soft-thresholding. The threshold is derived in a Bayesian framework, and the prior used on the wavelet coefficients is the generalized Gaussian distribution (GGD) widely used in image processing applications. The proposed threshold is simple and… (More)

- Steven McCanne, Van Jacobson, Martin Vetterli
- SIGCOMM
- 1996

State of the art, real-time, rate-adaptive, multimedia applications adjust their transmission rate to match the available network capacity. Unfortunately, this source-based rate-adaptation performs poorly in a heterogeneous multicast environment because there is no single target rate --- the conflicting bandwidth requirements of all receivers cannot be… (More)

- Minh N. Do, Martin Vetterli
- IEEE Trans. Image Processing
- 2002

We present a statistical view of the texture retrieval problem by combining the two related tasks, namely feature extraction (FE) and similarity measurement (SM), into a joint modeling and classification scheme. We show that using a consistent estimator of texture model parameters for the FE step followed by computing the Kullback-Leibler distance (KLD)… (More)

- Martin Vetterli, Pina Marziliano, Thierry Blu
- IEEE Trans. Signal Processing
- 2002

Consider classes of signals which have a ̄nite number of degrees of freedom per unit of time, and call this number the rate of innovation of a signal. Examples of signals with ̄nite rate of innovation include stream of Diracs (e.g. the Poisson process), non-uniform splines and piecewise polynomials. Eventhough these signals are not bandlimited, we show that… (More)

- S. Grace Chang, Bin Yu, Martin Vetterli
- IEEE Trans. Image Processing
- 1998

The method of wavelet thresholding for removing noise, or denoising, has been researched extensively due to its effectiveness and simplicity. Much of the literature has focused on developing the best uniform threshold or best basis selection. However, not much has been done to make the threshold values adaptive to the spatially changing statistics of… (More)

- Henri Dubois-Ferrière, Matthias Grossglauser, Martin Vetterli
- MobiHoc
- 2003

We propose FResher Encounter SearcH (FRESH), a simple algorithm for efficient route discovery in mobile ad hoc networks. Nodes keep a record of their most recent encounter times with all other nodes. Instead of searching for the destination, the source node searches for any intermediate node that encountered the destination more recently than did the source… (More)

- Martin Vetterli, Cormac Herley
- IEEE Trans. Signal Processing
- 1992

Wavelets, filter banks and multiresolution signal analysis, have been used independently in the fields of applied mathematics, computer vision and signal processing. It is interesting to note that they performed similar functions in different fields. It is recently, that they converged to form a single theory. In the paper, it is shown that the fundamental… (More)

- Kannan Ramchandran, Martin Vetterli
- IEEE Trans. Image Processing
- 1993

A fast rate-distortion (R-D) optimal scheme for coding adaptive trees whose individual nodes spawn descendents forming a disjoint and complete basis cover for the space spanned by their parent nodes is presented. The scheme guarantees operation on the convex hull of the operational R-D curve and uses a fast dynamic programing pruning algorithm to markedly… (More)