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Time-resolved femtosecond stimulated Raman spectroscopy (FSRS) is a powerful tool for investigating ultrafast structural and vibrational dynamics in light absorbing systems. However, the technique generally requires exposing a sample to…
The ability to enhance resonant signals and eliminate the non-resonant background is analyzed for Coherent Anti-Stokes Raman Scattering (CARS). The analysis is done at a specific frequency as well as for broadband excitation using…
Raman spectroscopy is widely applied to detect different chemical compounds in organic matter and create label-free high-resolution maps on the level of separate cells. The main advantage of this technique is the possibility to study…
Raman spectroscopy is a well established tool for the analysis of vibration spectra, which then allow for the determination of individual substances in a chemical sample, or for their phase transitions. In the…
Compressive Raman is a recent framework that allows for large data compression of microspectroscopy during its measurement. Because of its inherent multiplexing architecture, it has shown imaging speeds considerably higher than conventional…
In two-dimensional spectrographs, the optical distortions in the spatial and dispersion directions produce variations in the sub-pixel sampling of the background spectrum. Using knowledge of the camera distortions and the curvature of the…
Raman spectroscopy stands as a cornerstone technique for probing collective excitations and emergent quantum phases in solids. While polarization-resolved Raman scattering has been widely used to extract symmetry information of eigenmodes,…
Raman spectroscopy is a powerful tool for characterizing the local properties of graphene. Here, we introduce a method for evaluating unknown strain configurations and simultaneous doping. It relies on separating the effects of hydrostatic…
Image foreground extraction is a classical problem in image processing and vision, with a large range of applications. In this dissertation, we focus on the extraction of text and graphics in mixed-content images, and design novel…
Coherent anti-Stokes Raman scattering (CARS) microspectroscopy has demonstrated significant potential for biological and materials imaging. To date, however, the primary mechanism of disseminating CARS spectroscopic information is through…
Fluorescence microscopy is widely used for the study of biological specimens. Deconvolution can significantly improve the resolution and contrast of images produced using fluorescence microscopy; in particular, Bayesian-based methods have…
Despite being applied with success in many fields of materials science, Raman spectroscopy is not yet determinant in the study of electroceramics. Recent experimental and theoretical developments, however, should increase the popularity of…
Fashion understanding is a hot topic in computer vision, with many applications having great business value in the market. Fashion understanding remains a difficult challenge for computer vision due to the immense diversity of garments and…
We present a signal-foreground separation algorithm for filtering observational data to extract spectral distortions of the cosmic microwave background (CMB). Our linear method, called the least response method (LRM), is based on the idea…
21cm tomography promises to be a powerful tool for estimating cosmological parameters, constraining the epoch of reionization, and probing the so-called dark ages. However, realizing this promise will require the extraction of a…
We present results of Raman spectroscopic studies of urine to determine the suitability of near-infrared Raman spectroscopy for quantitative estimation of urinary urea. The Raman spectra were acquired from the urine samples with an inbuilt…
Recent work on background subtraction has shown developments on two major fronts. In one, there has been increasing sophistication of probabilistic models, from mixtures of Gaussians at each pixel [7], to kernel density estimates at each…
Background Subtraction (BS) is one of the key steps in video analysis. Many background models have been proposed and achieved promising performance on public data sets. However, due to challenges such as illumination change, dynamic…
Background treatment is crucial to extract physics from precision experiments. In this paper, we introduce a novel method to assign each event a signal probability. This could then be used to weight the event's contribution to the…
For many tracking and surveillance applications, background subtraction provides an effective means of segmenting objects moving in front of a static background. Researchers have traditionally used combinations of morphological operations…