Sparse Orthonormal Transforms (SOT) has recently been proposed as a data compression method that can achieve sparser representations in transform domain. Given initial conditions,...
Sparsity in the eigenspace of signal covariance matrices is exploited in this paper for compression and denoising. Dimensionality reduction (DR) and quantization modules present i...
We propose an novel method of computing and storing DataCubes. Our idea is to use Bayesian Networks, which can generate approximate counts for any query combination of attribute v...
Hashes can be used to provide authentication of multimedia contents. In the case of images, a hash can be used to detect whether the data has been modified in an illegitimate way....
Marco Tagliasacchi, Giuseppe Valenzise, Stefano Tu...
Abstract--This paper develops an optimal decentralized algorithm for sparse signal recovery and demonstrates its application in monitoring localized phenomena using energy-constrai...