177 citations · 608 across the 34 of their papers we have counts for
4 papers · 1 filter
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…
Smoothness-Constrained Image Recovery from Block-Based Random Projections
Giulio Coluccia, Diego Valsesia, Enrico Magli
In this paper we address the problem of visual quality of images reconstructed from block-wise random projections. Independent reconstruction of the blocks can severely affect visu…
Spatially Scalable Compressed Image Sensing with Hybrid Transform and Inter-layer Prediction Model
Diego Valsesia, Enrico Magli
Compressive imaging is an emerging application of compressed sensing, devoted to acquisition, encoding and reconstruction of images using random projections as measurements. In thi…
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…