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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 ...
Digital images are becoming increasingly successful thanks to the development and the facilitated access to systems permitting their generation (i.e. camera, scanner, imaging software, etc). A digital image basically corresponds to a 2D discrete set of reg ...
This paper investigates video coding with wavelet transforms applied in the temporal direction of a video sequence. The wavelets are implemented with the lifting scheme in order to permit motion compensation between successive pictures. We generalize the c ...
{W}e compare four local feature extraction techniques for the task of face verification, namely (ordered in terms of complexity): raw pixels, raw pixels with mean removal, 2D Discrete Cosine Transform (DCT) and local Principal Component Analysis (PCA). The ...
This paper presents a new approach toward automatic annotation of meetings in terms of speaker identities and their locations. This is achieved by segmenting the audio recordings using two independent sources of information : magnitude spectrum analysis an ...
This paper proposes a universal variable-length lossless compression algorithm based on fountain codes. The compressor concatenates the Burrows-Wheeler block sorting transform (BWT) with a fountain encoder, together with the closed-loop iterative doping al ...
We present complex rotation-covariant multiresolution families aimed for image analysis. Since they are complex-valued functions, they provide the important phase information, which is missing in the discrete wavelet transform with real wavelets. Our basis ...
The work presented in this paper extends the concept of sub-band video coding based on a 3D wavelet transform to a more adaptive approach. A formal comparison is presented between the performances inferred by the use of the 3D wavelet transform and the use ...
In this paper, we revisit wavelet theory starting from the representation of a scaling function as the convolution of a B-spline (the regular part of it) and a distribution (the irregular or residual part). This formulation leads to some new insights on wa ...
Statistical Parametric Mapping (SPM) is a widely deployed tool for detecting and analyzing brain activity from fMRI data. One of SPM's main features is smoothing the data by a Gaussian filter to increase the SNR. The subsequent statistical inference is bas ...
