| L. J. van Vliet. Grey-Scale Measurements in Multi-Dimensional Digitized Images. PhD thesis, Pattern Recognition Group, Delft University of Technology, Delft, 1993. 8 |
....and that chosen by the experimenter need not be the same. Furthermore, it is shown how the probability of resolution as a function of the SNR can be computed. Special attention is paid to imaging systems with a Gaussian PSF, since in practice many PSF s can be well approximated by a Gaussian one [10]. II. THE PARAMETRIC MODEL AND THE CRITERION OF GOODNESS OF FIT Suppose that a set of observations on a one dimensional (1 D) composite intensity distribution in the image of two point sources is available and that the following two point image model [11] 1) is fitted to the observations with ....
L. J. van Vliet, "Grey-scale measurements in multi-dimensional digitized images," Ph.D. dissertation, Delft Univ. Press, Delft, The Netherlands, 1993.
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L. J. van Vliet. Grey-Scale Measurements in Multi-Dimensional Digitized Images. PhD thesis, Pattern Recognition Group, Delft University of Technology, Delft, 1993. 8
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L.J. van Vliet. Grey-Scale Measurements in Multi-Dimensional Digitized Images. PhD thesis, Delft University of Technology, Delft, The Netherlands, October 1993.
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van Vliet, L.J.: Grey Scale Measurements in Multi Dimensional Dig' ized ImagH' PhD thesis, Pattern Recog ition Group, Faculty of Applied Physics, Delft Univer sity of Technolog , Delft (1993)
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L.J. van Vliet. Grey-Scale Measurements in Multi-Dimensional Digitized Images. PhD thesis, Delft University of Technology, Delft, The Netherlands, October 1993.
No context found.
L. J. van Vliet. Grey-Scale Measurements in Multi-Dimensional Digitized Images. PhD thesis, Pattern Recog nition Group, Delft University of Technolog y, Delft, 1993.
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Van Vliet, L.J., Grey-scale measurements in multi-dimensional digitized images, PhD Thesis: Delft University of Technology, 1993.
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Van Vliet, L.J. Grey-Scale Measurements in MultiDimensional Digitized Images. Ph.D. thesis, Delft University of Technology, The Netherlands. 1993
.... localization of curved edges uses a nonlinear combination of Gaussian derivatives [4] Geometric object features such as perimeter length in 2 D, curve length and surface area in 3 D, and shape descriptors such as bending energy and Euler number can be measured using Gaussian derivative filters [5]. Local anisotropy and orientation can be measured in a Gaussian smoothed tensor image constructed from the dyadic product of a gradient vector with itself [6, 7] These applications will benefit from a recursive implementation of Gaussian derivative filters. Recursive filters are fast and ....
L.J. van Vliet, Grey-Scale Measurements of MultiDimensional Digitized Images, Delft Univ. Press, 1993.
....(1995) 139 151 1. Introduction Gaussian filters have assumed a central role in image filtering because of research in models of human vision [6] methods for edge detection [2, 7] results in scale space [5, 14] and techniques for accurate measurement of analog quantities based on digital data [11, 12]. The implementation of the Gaussian filter in one or more dimensions has typically been done as a convolution with samples of the required Gaussian (Eq. 1) as repeated convolutions with a simpler filter such as a uniform filter (Eq. 2) or as a recursive filtering with an approximation to ....
L.J. Van Vliet, Grey-scale measurements in multi-dimensional digitized images, Ph.D Thesis, Delft University of Technology, 1993.
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