Name
Abstract | ||
|---|---|---|
Coded aperture compressive spectral imagers allow capturing spectral imaging information of a 3D cube with just a single 2D measurement of the coded and spectrally dispersed source field. These imagers systems often rely on existing FPA detectors, SLMs, and micro mirror devices, which are often mismatched in pitch size and pixel resolution. A traditional solution consists on grouping several pixels in square features with the aim to find a match between them. As a result, the resolution of the reconstructions decreases significantly. To overcome these hardware constraints, this paper develops a new model by which the high resolution of the coding and detector elements are fully exploited. Real reconstructions show the improvement and resolution gain achieved with the proposed approach compared with the grouping-pixel traditional solution. |
Year | Venue | Keywords |
|---|---|---|
2015 | 2015 IEEE GLOBAL CONFERENCE ON SIGNAL AND INFORMATION PROCESSING (GLOBALSIP) | Spectral Imaging, compressive sensing, hyper-spectral imaging, coded aperture |
Field | DocType | Citations |
Iterative reconstruction,Aperture,Computer vision,Full spectral imaging,Spectral imaging,Coded aperture,Computer science,Pixel,Artificial intelligence,Image resolution,Detector | Conference | 0 |
PageRank | References | Authors |
0.34 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Laura V. Galvis Carreño | 1 | 95 | 5.44 |
| Henry Arguello | 2 | 32 | 5.39 |
| Gonzalo R. Arce | 3 | 1061 | 134.94 |