DISP Projects

Coded Aperture Snapshot Spectral Imagers (CASSI)

Multi-aperture Imaging Systems

Evolving from the COMP-I (Compressive Optical MONTAGE Photography Initiative), the DISP Multi-Aperture Imaging Project focuses on new applications for these systems. Initially, thin imaging was the primary motivator, and arrays of short focal length lenses were used to miniaturize cameras.

We now are exploring the use of multi-aperture imaging for extended depth of field and increased FOV (field of view). A shorter focal length lens will inherently have a greater depth of field. However, we are interested in more advanced designs such as combining lenses of differing focal lengths on a single array. Additionally, orienting lenses to face different directions provides increased system FOV. We can improve the limited FOV of conventional cameras.

Finally, compressive imaging is one of the most interesting research areas. In conjunction with focal plane research, we are creating systems that introduce data compression in the measurement layer for both static and video imaging.

Tissue Spectroscopy

We have been involved in the study of aperture coded systems. These systems differ from conventional slit-based spectrometers by replacing the input slit with a mathematically well-defined code. The binary-valued codes, such as the Hadamard matrices, have a higher throughput in comparison to conventional systems without sacrificing resolution. Since at the focal plane of a computational sensor, we measure a convolution between the source and input aperture, inversion becomes a computational problem. Some inversion techniques have included iterative algorithms such as nonnegative least squares (NNLS), expectation maximization and principle component analysis (PCA) and multiple linear regression (MLR) for concentration estimation of target Raman active signals in tissue phantoms. The Hadamard-mask multiple-channel Raman spectrometer can be used as a portable, low-cost, and non-invasive solution for biomedical diagnostics.

Compressive Holography

We demonstrate that decompressive inference enables 3D tomography from a single 2D monochromatic digital hologram. In compressive sensing, sparse signals in some basis, sampled by multiplex encodings, may be accurately infered with high probability using many fewer measurements than suggested by Shannons sampling theorem. Holography has general advantages in compressive optical imaging since it is an interferometric modality in which both the amplitude and the phase of a field can be obtained. The complex-valued encodings may provide a more direct application of compressive sensing.

Computational Spectral Microscopy

We have extended the use of high throughput spectrometers to spectral microscopy applications. A pushbroom scanned high-throughput spectrometer on the back-end of a microscope creates a three dimensional cube (2D spatial, 1D spectral) from a fluorescent fixed-cellular assay. Current system designs include a snapshot dual disperser (DD-CASSI) architecture. Our goal includes imaging dynamic cellular events using fluorescence microscopy as a tool. The benefits of these computational spectral imagers applied to microscopy include high throughput analysis and a higher spectral measurement when compared to conventional spectral imaging systems.