Compressive sensing (CS) has recently emerged and is now a subject of increasing research and discussion, undergoing
significant advances at an incredible pace.
The novel theory of CS provides a fundamentally new approach to data acquisition which overcomes the common
wisdom of information theory, specifically that provided by the Shannon-Nyquist sampling theorem. Perhaps
surprisingly, it predicts that certain signals or images can be accurately, and sometimes even exactly, recovered from
what was previously believed to be highly incomplete measurements (information).
As the requirements of many applications nowadays often exceed the capabilities of traditional imaging architectures,
there has been an increasing deal of interest in so-called computational imaging (CI). CI systems are hybrid imagers in
which computation assumes a central role in the image formation process.
Therefore, in the light of CS theory, we present a transmissive single-pixel camera that integrates a liquid crystal
display (LCD) as an incoherent random coding device, yielding CS-typical compressed observations, since the
beginning of the image acquisition process.
This camera has been incorporated into an optical microscope and the obtained results can be exploited towards the
development of compressive-sensing-based cameras for pixel-level adaptive gain imaging or fluorescence microscopy.