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David C. Munson
Researcher at University of Michigan
Publications - 119
Citations - 3630
David C. Munson is an academic researcher from University of Michigan. The author has contributed to research in topics: Synthetic aperture radar & Radar imaging. The author has an hindex of 25, co-authored 119 publications receiving 3484 citations. Previous affiliations of David C. Munson include University of Illinois at Urbana–Champaign & University of Texas at Austin.
Papers
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A tomographic formulation of spotlight-mode synthetic aperture radar
TL;DR: In this article, a projection-slice theorem from computer-aided tomograpy (CAT) is used to analyze the signal recorded at each SAR transmission point, which is modeled as a portion of the Fourier transform of a central projection of the imaged ground area.
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A generalization of median filtering using linear combinations of order statistics
TL;DR: In this paper, the authors consider a class of nonlinear filters whose output is given by a linear combination of the order statistics of the input sequence, and choose the coefficients in the linear combination to minimize the output MSE for several noise distributions.
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The Effect of Median Filtering on Edge Estimation and Detection
TL;DR: Noise images prefiltered by median filters defined with a variety of windowing geometries are used to support the analysis and it is found that median prefiltering improves the performance of both thresholding and zero-crossing based edge detectors.
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A signal processing view of strip-mapping synthetic aperture radar
David C. Munson,R.L. Visentin +1 more
TL;DR: The authors derive the fundamental strip-mapping SAR (synthetic aperture radar) imaging equations from first principles and show that the resolution mechanism relies on the geometry of the imaging situation rather than on the Doppler effect.
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SAR Image Autofocus By Sharpness Optimization: A Theoretical Study
TL;DR: A theoretical analysis of metric-based SAR autofocus techniques using simple image models shows that the objective function has a special separble property through which it can be well approximated locally by a sum of 1-D functions of each phase error component simultaneously.