Spread Transform (ST) is a quantization watermarking algorithm in which vectors of the wavelet coefficients of a host work are quantized, using one of two dithered quantizers, to ...
We present a supervised classification model based on a variational approach. This model is specifically devoted to textured images. We want to get a partition of an image, compos...
In this paper, we first propose a new family of geometrical image transforms that decompose images both radially and angularly. Our construction comprises two stages of filter ban...
A degree-k zerotree model is presented, in order to quantify the coding power of zerotrees in wavelet-based image coding. Based on the model, the coding behaviors of modern zerotr...
We investigate reducing the dimensionality of image sets by using principal component analysis on wavelet coefficients to maximize edge energy in the reduced dimension images. Lar...
Wavelet domain statistical modeling of images has focused on modeling the peaked heavy-tailed behavior of the marginal distribution and on modeling the dependencies between coeffi...
We consider the problem of estimating and encoding depth maps from multiple views in the context of 3D-TV with free-viewpoint rendering. We propose a novel codec based on the Rate...
In this paper, We propose an efficient compression method to encode the geometry of 3D mesh sequences of objects sharing the same connectivity. Our approach is based on the cluste...
Here we propose an alternative non-explicit way to take into account the relations among wavelet coefficients in natural images for denoising: we use Support Vector Machines (SVM)...
Valero Laparra, Juan Gutierrez, Gustavo Camps-Vall...