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Full-Text Articles in Engineering
Evaluation Of A Maximum A-Posteriori Slope Estimator For A Hartmann Wavefront Sensor, Troy B. Van Caster
Evaluation Of A Maximum A-Posteriori Slope Estimator For A Hartmann Wavefront Sensor, Troy B. Van Caster
Theses and Dissertations
Current methods for estimating the wavefront slope at the aperture of a telescope using a Hartmann wavefront sensor are based upon a centroid shift estimator. The centroid shift estimator determines the displacement, or shift, of the centroid off the optical axis using a moment calculation of the intensity distributions recorded in each subaperture. This centroid shift is proportional to the average slope of the wavefront in each subaperture. A maximum a-posteriori (MAP) slope estimator takes advantage of a-priori knowledge of the wavefront slope statistics and total irradiance falling on the subaperture detector arrays when determining the shift estimate. In order …
Joint-Transform Correlator Architecture For Wavelet Feature Extraction, Samuel Peter Kozaitis, Mark A. Getbehead, Wesley E. Foor
Joint-Transform Correlator Architecture For Wavelet Feature Extraction, Samuel Peter Kozaitis, Mark A. Getbehead, Wesley E. Foor
Electrical Engineering and Computer Science Faculty Publications
A version of an image consisting of multiple wavelet scales allows for more flexible feature extraction when compared to the use of one wavelet scale. We proposed an imaging system based on a multiple-input joint-transform correlator, that could be used for multiple wavelet-scale analysis of an input image. Given a single input image and wavelet, for m wavelet scales, m versions of the wavelet and m copies of the input image were generated using conventional optics that are used as inputs to a joint wavelet-transform correlator. The output consisted of 4 m - 1 correlation results, one of which is …
Multispectral Image Feature Extraction By The Joint Wavelet-Transform Correlator, Samuel Peter Kozaitis, Mark A. Getbehead, Wesley E. Foor
Multispectral Image Feature Extraction By The Joint Wavelet-Transform Correlator, Samuel Peter Kozaitis, Mark A. Getbehead, Wesley E. Foor
Electrical Engineering and Computer Science Faculty Publications
A multispectral version of an image consisting of multiple wavelet components allows for more flexible feature extraction when compared to the use of one wavelet component. We showed how a multiple-input joint wavelet- transform correlator could be used for multispectral analysis of an input image. For m wavelet scales, m versions of the wavelet and m copies of the input image were generated using conventional optics that are used as inputs to a joint wavelet-transform correlator. The output consisted of 4m-1 correlation results, one of which is the desired output. The space-bandwidth product of the system is the same as …