The feasibility of images reconstructed with the method of sieves
The concept of sieves has been applied with the Maximum likelihood Estimator (MLE) to image reconstruction. While it makes it possible to recover smooth images consistent with the data, the degree of smoothness provided by it is arbitrary. It is shown that the concept of feasibility is able to resolve this arbitrariness. By varying the values of parameters determining the degree of smoothness, one can generate images on both sides of the feasibility region, as well as within the region. Feasible images recovered by using different sieve parameters are compared with feasible results of other procedures. One- and two-dimensional examples using both simulated and real data sets are considered. 12 refs., 3 figs., 2 tabs.
- Research Organization:
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- DOE/ER
- DOE Contract Number:
- AC03-76SF00098
- OSTI ID:
- 6999351
- Report Number(s):
- LBL-27088; CONF-900143-34; ON: DE90011599
- Resource Relation:
- Journal Volume: 37; Journal Issue: 2; Conference: Institute for Electronic and Electrical Engineers (IEEE) nuclear science symposium, San Francisco, CA (USA), 15-19 Jan 1990
- Country of Publication:
- United States
- Language:
- English
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990200* - Mathematics & Computers