Patrice Brault

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— In this paper, a method for enhancing low contrast images is proposed. This method, called Gaussian Mixture Model based Contrast Enhancement (GMMCE), brings into play the Gaussian mixture modeling of histograms to model the content of the images. Based on the fact that each homogeneous area in natural images has a Gaussian-shaped histogram, it decomposes(More)
—Video compression has been investigated by means of analysis-synthesis, and more particularly by means of inpainting. The first part of our approach has been to develop the inpainting of DCT coefficients in an image. This has shown good results for image compression without overpassing todays compression standards like JPEG. We then looked at integrating(More)
Cauchy and conical wavelets have been constructed as a response to the lack of aperture selectivity of the Mor-let wavelet [1, 2]. Furthermore, they allow a very simple adjustment of their angular selectivity. On the other hand, the Morlet wavelet has been tuned to speed in the 90s [7] and its efficiency has been demonstrated for psychovisual analysis. It(More)
Motion analysis and in particular, speed and rotation analysis, has been introduced in the 80s using the continuous wavelet transform(CWT) with Morlet wavelets. The motion-tuned WT appeared to be an efficient framework and an alternative to the optical flow (OF), the block matching (BM) or the phase difference, for the study of motion. In particular it has(More)
Prediction methods by template matching are often mentioned to improve video coding efficiency. They are based on a Markovian model to find the most similar patterns of texture in previously encoded information. These kinds of methods are more efficient than H.264/AVC intra prediction modes in many cases, such as complex texture coding. However, the(More)
We describe a new fully unsupervised image segmenta-tion method based on a Bayesian approach and a Potts-Markov random field (PMRF) model that are performed in the wavelet domain. A Bayesian segmentation model, based on a PMRF in the direct domain, has already been successfully developed and tested. This model performs a fully unsupervised segmentation, on(More)
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