High-pass filtering has been shown to be a promising method for edge detection in optical scanning holography. By using a circular function as a pupil for the system, the radius of the circle can be varied to block out different ranges of frequencies. Implementing this system in simulation yields an interesting result, however. As the radius increases, a singular edge can split off into two edges instead. To understand the specific conditions under which this split occurs, Airy pattern filtering and single-sided filtering were implemented to analyze the results from the original high-pass simulation. These methods were tested with different input objects to assess any common patterns. Ultimately, no definitive answer was found, as Airy pattern filtering resulted in inconsistent results across different input objects, and single-sided filtering does not completely isolate the edge. Nonetheless, the documented results may aid a future understanding of this phenomenon. / Master of Science / Holograms are three-dimensional recordings of an object, reminiscent of how a photograph records a two-dimensional image of an object. Detecting edges in images and the reconstructed images from holograms can help us identify objects within the recorded image or hologram. In computer vision, common edge detection techniques involve analyzing the image's spatial frequency, or changes in relative intensity over space. One such technique is high-pass filtering, in which lower spatial frequencies are blocked out. High-pass filtering can also be applied to holographic imaging systems. However, when applying high-pass filtering to a holographic system, detected edges can split into two as higher frequencies are filtered out. This thesis examines the conditions for why this split-edge phenomenon occurs by modifying the original recorded object and the filtering mechanism, then analyzing the resultant holograms. While the results did not give a conclusive answer, they have been documented for the purpose of further research.

High-pass filtering that is one of the most efficient methods in removing long-period noise of accelerograms is investigated for its effect on nonlinear oscillator deformation response. Within this context, uncertainty in filter cut-off periods that would significantly modify the low-frequency content of accelerograms come into prominence for obtaining reliable long-period displacement response. Analog and digital ground-motion records from recently compiled Turkish strong-motion database are used and these records are high-pass filtered with a consistent methodology by randomly generated filter cut-offs that represent different filter cut-off decisions of the analysts. The uncertainty in inelastic spectral and residual displacements (SDIE and SDR, respectively) due to variations in filter cut-offs is examined to derive the usable period ranges where the effect of high-pass filtering is tolerable. Non-degrading, stiffness degrading and stiffness and strength degrading oscillator behavior are considered in these analyses. The level of nonlinear behavior in single degree of freedom (SDOF) response is described by varying the yield strength (R, normalized yield strength) and displacement ductility (&micro / ) levels. The usable period ranges that depend on magnitude, recording quality, level of inelasticity and level of degradation are determined for SDIE through robust probabilistic methodologies.