Hyperspectral passive satellite imaging via compressive sensing (HPSI-CS)

According to recent research findings, signal acquisition can be performed at sampling frequencies far below the minimal frequency dictated by Shannon`s theorem, a concept called "compressive sampling" (CS). This technique can be applied to signals that exhibit some correlation, a feature indicated as sparsity. CS brings many potential advantages to hyperspectral satellite imaging, since high spectral/spatial resolution can be reached with fewer detectors, lower memory capacity, and narrower down-link bandwidth. This project addresses the feasibility and essential technology features of CS as applied to Earth Observation. The following issues will be investigated: development of high frame-rate electro-optical light modulators, adaptation of high-frequency light detectors, quality of reconstructed images, and corresponding reconstruction algorithms. A laboratory test-bed will be set up and used to test the CS technology.