Coded Memory Effect Imaging

Imaging through scattering media is of great interest and has important applications in many fields such as biological, medical, and astronomical imaging. However performing imaging with scattered light is challenging because the complex and random modulation imposed upon the light by the scatterer. In this dissertation, I introduce a new techinuqe to reconstruct an object hidden behind a scattering media. I demonstrate experimentally that the temporal or spectral information of the object can be recovered from a single measurement. More important, the reconstruction process does not rely on the prior knowledge or access to the scattering media.

Conventional imaging methods such as wavefront shaping and adptive optics have been developed to conquer the imaging through scattering media challenge. However those approaches usually require access to the scattering media, which is impractical in many imaging scenarios. Meanwhile the memory effect (ME) imaging is capable of recovering the object from one single shot of random speckle measurement without access to the scattering media when the size of the object is within the memory effect range of the scatterer. However, memory effect imaging techniques have been limited to static and grayscale imaging, therefore a tremendous amount of information of the light is wasted. To overcome this disadvantage I introduce coding and compressed sensing to realize snapshot imaging through scattering media.

In this dissertation I present the technique details of the single shot non-invasive method for imaging through scattering media. Optical implementations and experimental demonstrations of various cases such as dynamic object through dynamic/static diffuser and multi-spectral (discrete and continuous) object are provided in different chapters. The advantage of our technique such as high performance in an SNR-limited environment and high spectral resolution (comparing with the state-of-art method) are also introduced along with the experimental demonstrations.