Master of Science (M.S.), University of Dayton, 2018, Electro-Optics

In this thesis, Electro-Optic (EO) range signatures are obtained with a Short-Wave Infrared Super-Continuum Laser (SWIR-SCL) source. 3D printed canonical targets of interest are illuminated by the SWIR-SCL pulsed laser. The scattered laser light from the target is directly detected in mono-static and bi-static configurations with a fast, high bandwidth Indium Gallium Arsenide (InGaAs) PIN photodiode. Temporal pulse returns provide target shape, orientation, and surface roughness information. Spatial and temporal analysis of the collected intensity distribution is performed in MATLAB. Macro and micro surface properties are identified from the collected data by correlating pulse amplitude variations with known range scenes. Finally, range resolution improvement is investigated by means of Tomographic Reconstruction using Radon Transforms and by image processing techniques such as Deconvolution.

Committee: Edward Watson Ph.D. (Advisor); Paul McManamon Ph.D. (Committee Member); Joe Haus Ph.D. (Committee Member) Subjects: Computer Engineering; Electrical Engineering; Engineering; Experiments; Optics; Physics; Scientific Imaging

Doctor of Philosophy, The Ohio State University, 2007, Electrical Engineering

Electron paramagnetic resonance imaging (EPRI) is capable of measuring both endogenous and introduced free radical distributions in variety of biological systems. Despite the inherent potential, the broad use of EPRI is hampered by slow acquisition which can be the bottleneck for many biological applications where conditions may change over time. The objective of this work is to reduce the data acquisition time without degrading the reconstruction quality. First, we have modeled the data acquisition process for both spatial and spectral-spatial imaging in the form of Radon transform. Efficient-to-program expressions for Radon and inverse Radon transform for 2D, 3D, and 4D EPRI are derived. Second, we have proposed a method to uniformly distribute the data for both 3D and 4D EPRI which, from fewer projections, can generate reconstruction results which are better than those based on the existing nonuniform or partially uniform sampling techniques. The expected savings in the acquisition time offered by the suggested uniform sampling are 30% and 50% for 3D and 4D, respectively. In addition, we have also discussed existing uniform sampling methods and compared their performance with the suggested method using simulation and experimental data. Third, we have suggested a single-stage filtered backprojection reconstruction for 3D and 4D EPRI using the partial Radon transform for 4-fold acceleration. This substantial speed up further motivated us to reconsider the iterative reconstruction methods such as algebraic reconstruction which, despite having the superior performance in terms of reconstruction quality, have not been routinely used for 3D and 4D reconstructions due to their slow speeds. With the use of partial Radon transform, along with proper choice of interpolation type, the 3D iterative reconstruction time is reduced by more than 80%, which implies that a 64×64×64 image can be reconstructed from 150 projections using 100 iterations in approximately 10 minutes wit (open full item for complete abstract)

Committee: Bradley Clymer (Advisor) Subjects:

Master of Sciences, Case Western Reserve University, 2013, EECS - Electrical Engineering

If detected early, skin cancer has a 95-100% successful treatment rate; therefore early detection is crucial and several computer-aided methods have been developed to assist dermatologists. In skin images removing hairs without altering the lesion is important to effectively apply detection algorithms. This thesis focuses on the use of image processing techniques to remove hairs by identifying hair pixels contained within a binary image mask using the Generalized Radon Transform. The Radon Transform was adapted to find quadratic curves characterized by rotational angle and scaling. The method detects curved hairs in the image mask for removal and replacement through pixel interpolation. Implementing this technique in MATLAB gives the ability to perform tests rapidly on both simulated and actual images. The quadratic Radon transform performs well in curve detection; however, the research points out the need for better algorithms to improve hair masking, peak detection, and interpolation replacement.

Committee: Marc Buchner PhD (Advisor); Kenneth Loparo PhD (Committee Member); Vira Chankong PhD (Committee Member) Subjects: Electrical Engineering