29 citations · 89 across the 9 of their papers we have counts for
4 papers · 2 filters
Joint recovery algorithms using difference of innovations for distributed compressed sensing
Diego Valsesia, Giulio Coluccia, Enrico Magli
Distributed compressed sensing is concerned with representing an ensemble of jointly sparse signals using as few linear measurements as possible. Two novel joint reconstruction alg…
Progressive Compressed Sensing and Reconstruction of Multidimensional Signals Using Hybrid Transform/Prediction Sparsity Model
Giulio Coluccia, Simeon Kamden-Kuiteng, Andrea Abrardo +2
Compressed sensing (CS) is an innovative technique allowing to represent signals through a small number of their linear projections. Hence, CS can be thought of as a natural candid…
A Novel Progressive Image Scanning and Reconstruction Scheme based on Compressed Sensing and Linear Prediction
Giulio Coluccia, Enrico Magli
Compressed sensing (CS) is an innovative technique allowing to represent signals through a small number of their linear projections. In this paper we address the application of CS…
Graded Quantization: Democracy for Multiple Descriptions in Compressed Sensing
Diego Valsesia, Giulio Coluccia, Enrico Magli
The compressed sensing paradigm allows to efficiently represent sparse signals by means of their linear measurements. However, the problem of transmitting these measurements to a r…