RESUMEN
One challenge that has long held the attention of scientists is that of clearly seeing objects hidden by turbid media, as smoke, fog or biological tissue, which has major implications in fields such as remote sensing or early diagnosis of diseases. Here, we combine structured incoherent illumination and bucket detection for imaging an absorbing object completely embedded in a scattering medium. A sequence of low-intensity microstructured light patterns is launched onto the object, whose image is accurately reconstructed through the light fluctuations measured by a single-pixel detector. Our technique is noninvasive, does not require coherent sources, raster scanning nor time-gated detection and benefits from the compressive sensing strategy. As a proof of concept, we experimentally retrieve the image of a transilluminated target both sandwiched between two holographic diffusers and embedded in a 6mm-thick sample of chicken breast.
RESUMEN
In computational imaging by pattern projection, a sequence of microstructured light patterns codified onto a programmable spatial light modulator is used to sample an object. The patterns are used as generalized measurement modes where the object information is expressed. In this Letter, we show that the resolution of the recovered image is only limited by the numerical aperture of the projecting optics regardless of the quality of the collection optics. We provide proof-of-principle experiments where the single-pixel detection strategy outperforms the resolution achieved using a conventional optical array detector for optical imaging. It is advantageous in the presence of real-world conditions, such as optical aberrations and optical imperfections in between the sample and the sensor. We provide experimental verification of image retrieval even when an optical diffuser prevents imaging with a megapixel array camera.
