29 citations · 89 across the 9 of their papers we have counts for
9 papers
Graded quantization for multiple description coding of compressive measurements
Diego Valsesia, Giulio Coluccia, Enrico Magli
Compressed sensing (CS) is an emerging paradigm for acquisition of compressed representations of a sparse signal. Its low complexity is appealing for resource-constrained scenarios…
Operational Rate-Distortion Performance of Single-source and Distributed Compressed Sensing
Giulio Coluccia, Aline Roumy, Enrico Magli
We consider correlated and distributed sources without cooperation at the encoder. For these sources, we derive the best achievable performance in the rate-distortion sense of any…
Compressive Hyperspectral Imaging Using Progressive Total Variation
Simeon Kamdem Kuiteing, Giulio Coluccia, Alessandro Barducci +2
Compressed Sensing (CS) is suitable for remote acquisition of hyperspectral images for earth observation, since it could exploit the strong spatial and spectral correlations, llowi…
Exact Performance Analysis of the Oracle Receiver for Compressed Sensing Reconstruction
Giulio Coluccia, Aline Roumy, Enrico Magli
A sparse or compressible signal can be recovered from a certain number of noisy random projections, smaller than what dictated by classic Shannon/Nyquist theory. In this paper, we…
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…