A new iterative algorithm for image restoration and point spread function (PSF) estimation is presented. The method initially estimates the PSF and the original image using the expectationmaximization (EM) method. Th...
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ISBN:
(纸本)0819407437
A new iterative algorithm for image restoration and point spread function (PSF) estimation is presented. The method initially estimates the PSF and the original image using the expectationmaximization (EM) method. The resulting image estimate is then refined by using the adaptive Row Action Projection (RAP) algorithms which is based on the theory of Projection Onto Convex Sets (POCS). The new implementation of the RAP algorithm can be performed efficiently in parallel and facilitates locally adaptive constraints and cycling strategies. The PSF is re-estimated using a least square technique. Computer simulations illustrate the new method to be very competitive in restoring degraded images and estimating the PSF from noisy blurred images with unknown PSF.
A Bayesian approach to image reconstruction from emission tomography image is presented in which the image is modeled using a joint Gibbs distribution of emission intensities and line processes. The line process repre...
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ISBN:
(纸本)0819405515
A Bayesian approach to image reconstruction from emission tomography image is presented in which the image is modeled using a joint Gibbs distribution of emission intensities and line processes. The line process represents the presence or absence of discontinuities between each neighboring pair of pixels. It is introduced to avoid the smoothing across discontinuities, which commonly occurs in Bayesian image estimation when a line process is not included. Two algorithms for MAP estimation over both intensity and line processes are presented. Both methods employ the generalized EM (GEM) algorithm to avoid direct optimization over the posterior distribution which does not share the Markovian property of the prior. The M-step of the GEM algorithm of the MAP estimation problem requires optimization over a function which has the appealing property that the neighborhood is identical to that of the prior. During the M-step both the intensity and line processes are updated. This is achieved in two stages. In the M1-step the intensities are updated, while holding the line process constant, using a gradient descent method. In the M2-step the line process is updated, with the intensity process held constant. Two alternative M2-steps are described in the paper. The use of a line process in the image model also provides a natural framework for the incorporation of a priori information from other modalities. In this case, boundaries may be found from MR or CT images and used as known line processes in the image estimation procedure.
The possibilities of this learning system made for interferogram and speckle-correlogram processing are reviewed. Its easy learning and robustness seem to be useful both for industrial applications and for experiment.
ISBN:
(纸本)0819405191
The possibilities of this learning system made for interferogram and speckle-correlogram processing are reviewed. Its easy learning and robustness seem to be useful both for industrial applications and for experiment.
An iterative solution is given for solving deblurring problems having nonnegativity constraints through the use of methods motivated by tomographic imaging.
ISBN:
(纸本)0819404098
An iterative solution is given for solving deblurring problems having nonnegativity constraints through the use of methods motivated by tomographic imaging.
We report on the behavior ofthe linear maximum a posteriori (MAP) tomographic reconstruction technique as a function of the assumed rms noise αn in the measurements, which specifies the degree of confidence ...
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ISBN:
(纸本)0819402753
We report on the behavior ofthe linear maximum a posteriori (MAP) tomographic reconstruction technique
as a function of the assumed rms noise αn in the measurements, which specifies the degree of confidence in
the measurement data. The unconstrained MAP reconstructions are evaluated on the basis of the performance
of two related tasks; object detection and amplitude estimation. It is found that the detectability
of medium-sized discs remains constant up to relatively large αn before slowly diminishing. However, the
amplitudes of the discs estimated from the MAP reconstructions increasingly deviate from their actual
values as αn increases.
This paper briefly describes the stochastic image model and the image analysis technique for X-ray CT, and then validates the use of this model and technique to MRI modality. The results of image analysis from the use...
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ISBN:
(纸本)0819404101
This paper briefly describes the stochastic image model and the image analysis technique for X-ray CT, and then validates the use of this model and technique to MRI modality. The results of image analysis from the use of X-ray CT and MRI are included to show the promise and the effectiveness of the developed technique.
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