In this paper, following the Compressed Sensing (CS) paradigm, we study the problem of recovering sparse or compressible signals from uniformly quantized measurements. We present ...
In this paper, we propose a new variational decomposition model which splits an image into two components: a first one containing the structure and a second one the texture or nois...
The tree-structured wavelet transform has received a lot of attention and has found successful applications in signal denoising, image coding, image analysis, etc. In this paper, ...
Reducing the dimension of local descriptors in images is useful to perform pixels comparison faster. We show here that, for enhancing and optimising the computation of the NL-mean...
We are motivated by a recently developed nonlinear inverse scale space method for image denoising [5, 6], whereby noise can be removed with minimal degradation. The additive noise ...