Comparison of Hadamard imaging and compressed sensing for low resolution hyperspectral imaging

Image multiplexing is the technique of using combination patterns to measure multiple pixels with one sensor. Hyperspectral imaging is acquiring images with full spectra at each pixel. Using a single point spectrometer and light modulation we perform multiplexed hyperspectral imaging. We compare two forms of multiplexing, namely Hadamard imaging and compressed sensing, at low resolution. We show that Hadamard imaging is the more accurate and precise method. The primary benefit of compressed sensing is that generally a reduced number of acquisitions are necessary for accurate reconstruction. Reasonable reconstruction was achieved with compressed sensing. For example at approximately three fifths the number of measurements for Hadamard imaging, the SNR of compressed sensing approached that of Hadamard imaging with about 15% reconstruction error.