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Full-Text Articles in Electrical and Computer Engineering
Trigonometric Transforms For Image Reconstruction, Thomas M. Foltz
Trigonometric Transforms For Image Reconstruction, Thomas M. Foltz
Theses and Dissertations
This dissertation demonstrates how the symmetric convolution-multiplication property of discrete trigonometric transforms can be applied to traditional problems in image reconstruction with slightly better performance than Fourier techniques and increased savings in computational complexity for symmetric point spread functions. The fact that the discrete Fourier transform a circulant matrix provides an alternate way to derive the symmetric convolution-multiplication property for discrete trigonometric transforms. Derived in this manner, the symmetric convolution-multiplication property extends easily to multiple dimensions and generalizes to multidimensional asymmetric sequences. The symmetric convolution-multiplication property allows for linear filtering of degraded images via point-by-point multiplication in the transform domain …
Linear Reconstruction Of Non-Stationary Image Ensembles Incorporating Blur And Noise Models, Stephen D. Ford
Linear Reconstruction Of Non-Stationary Image Ensembles Incorporating Blur And Noise Models, Stephen D. Ford
Theses and Dissertations
Two new linear reconstruction techniques are developed to improve the resolution of images collected by ground-based telescopes imaging through atmospheric turbulence. The classical approach involves the application of constrained least squares (CLS) to the deconvolution from wavefront sensing (DWFS) technique. The new algorithm incorporates blur and noise models to select the appropriate regularization constant automatically. In all cases examined, the Newton-Raphson minimization converged to a solution in less than 10 iterations. The non-iterative Bayesian approach involves the development of a new vector Wiener filter which is optimal with respect to mean square error (MSE) for a non-stationary object class degraded …