Browsing by Author "Lu, Liyang"

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    Compressive Hyperspectral Microscopy of Scattering and Fluorescence of Nanoparticles
    (American Chemical Society, 2022) Xu, Yibo; Lu, Liyang; Giljum, Anthony; Payne, Courtney M.; Hafner, Jason H.; Ringe, Emilie; Kelly, Kevin F.
    Hyperspectral imaging in optical microscopy is of importance in the study of various submicron physical and chemical phenomena. However, its practical application is still challenging because the additional spectral dimension increases the number of sampling points to be independently measured compared to two-dimensional (2D) imaging. Here, we present a hyperspectral microscopy system through passive illumination approach based on compressive sensing (CS) using a spectrometer with a one-dimensional (1D) detector array and a digital micromirror device (DMD). The illumination is patterned after the sample rather than on it, making this technique compatible with both dark-field and bright-field imaging. The DMD diffraction issue resulting from this approach has been overcome by a novel striped DMD pattern modulation method. In addition, a split pattern method is developed for increasing the spatial resolution when employing the DMD pattern modulation. The efficacy of the system is demonstrated on nanoparticles using two model systems: extended plasmonic metal nanostructures and fluorescent microspheres. The compressive hyperspectral microscopic system provides a fast, high dynamic range, and enhanced signal-to-noise ratio (SNR) platform that yields a powerful and low-cost spectral analytical system to probe the optical properties of a myriad of nanomaterial systems. The system can also be extended to wavelengths beyond the visible spectrum with greatly reduced expense compared to other approaches that use 2D array detectors.
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    Compressive Hyperspectral Video Detection and Imaging
    (2017-04-20) Lu, Liyang; Kelly, Kevin F.
    Hyperspectral video imaging remains a challenging task given the high dimensionality of the datasets and the limited imaging spatio-spectral-temporal tradeoffs via current methods. Yet, it has great potential in studying a variety of dynamic optical phenomena, both in microscopic and macroscopic systems. The first part of this thesis describes the design and implementation of spatially compressive hyperspectral imaging for dark-field and broad-band sum-frequency generation microscopy in order to capture and analyze different nanomaterial properties. Next, a compressive classification method using secant patterns is designed to perform task-aware compressive sensing. It achieves fast and efficient classification based on sampling but not full reconstruction using single-pixel camera hardware. Lastly, a novel compressive imaging system, the single-doxel imager (SDI), is demonstrated for four dimensional hyperspectral video imaging. It is uniquely based on a single light modulator and a single detector. By performing optical spatial and spectral modulations simultaneously with a set of designed spatio-spectral modulation patterns, it can encode hyperspectral information into a highly compressed sequence of measurements. Along with the novel optical design, a new compressive imaging reconstruction algorithm is also implemented, which is able to exploit the inherent redundancy in the 4D temporal-spatio-spectral datacube. Using this system, single-pixel hyperspectral video imaging that achieves a compression ratio of 900 to 1 is demonstrated.
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    Imaging Plasmons with Compressive Hyperspectral Microscopy
    (2015-04-23) Lu, Liyang; Kelly, Kevin F; Baraniuk, Richard G; Landes, Christy
    With the ability of revealing the interactions between objects and electromagnetic waves, hyperspectral imaging in optical microscopy is of great importance in the study of various micro/nano-scale physical and chemical phenomena. The conventional methods, however, require various scanning processes to acquire a complete set of hyperspectral data because of its 3-dimensional structure. As such the quality and efficiency of the data acquisition using these conventional scanning techniques is greatly limited by the detector sensitivity and low signal light intensity from the sample. To overcome such limitations, we applied compressive sensing theory to the hyperspectral imaging. The compressive imaging enhances the measurement signal-to-noise ratio by encoding and combining the spatial information of the sample to the detector, and a recovery algorithm is used to decode the detector outputs and reconstruct the image. A microscopy system based on this compressive hyperspectral imaging scheme was designed and implemented. Further analysis and discussion on the diffraction and interference phenomenon and a solution to the spectral distortion in this compressive sensing microscopy system are also presented. Experimental results of compressive dark-field scattering from gold nanobelts are presented, followed with an analysis on signal-to-noise ratio and a comparison with conventional scanning methods in measuring the plasmon resonances.