Graduate Thesis Or Dissertation
 

Pattern discovery in noisy images

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https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/pk02cf16m

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  • The Focused Ion Beam (FIB) tool is a versatile instrument for nano-machining in circuit editing. Circuit editing is one of the most important steps in the design of an electronic circuit on a chip. Circuit editing can be improved by imaging of silicon plates and analyzing the resultant images. However smaller features in FIB produce lower signal-to-noise (S/N) ratio in images, and thus render visual feedback increasingly difficult. For this Master thesis, we focus on analyzing a set of Focused Ion Beam grey valued images. Our goal is to reduce the noise in images, and apply an appropriate filter, for feature extraction. This is expected to allow us to see the significant features of the silicon plates. The main challenge is that the noise and its level are unknown. Also the significant features of the silicon plate are unknown. Therefore the problem that we face here is discovery of an unknown pattern in images, under unknown noise. We make the assumption that noise is a superposition of a Gaussian noise, Salt-and-Pepper noise and affine perturbations. We seek the significant features using a least squares optimization to solve for the latent affine transformation, and recover the most significant pattern in the images. The improved images enable the tool user to recognize critical features more reliably for circuit editing.
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