Abstract
The minimization of the weighted least-squares (WLS) measure has been established as a good technique for the selection of the regularization parameter associated with the constrained least-squares restoration approach. In this paper we study the WLS measure when linear and nonlinear estimators are considered. Nonlinear estimators become increasingly important in association with robust restoration schemes. Such estimators often lack analytic interpretation rendering the direct computation of the WLS measure useless. It is shown that the value minimizing the WLS measure can be approximated by the solution of a nonlinear equation. The approximation improves as the signal-to-noise ratio increases. The efficiency of this approximation is verified through restoration examples in Laplacian noise.
| Original language | English (US) |
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| Title of host publication | Proceedings - IEEE International Symposium on Circuits and Systems |
| Publisher | Publ by IEEE |
| Pages | 415-418 |
| Number of pages | 4 |
| Volume | 1 |
| ISBN (Print) | 0780312813 |
| State | Published - Jan 1 1993 |
| Event | 1993 IEEE International Symposium on Circuits and Systems - Chicago, IL, USA Duration: May 3 1993 → May 6 1993 |
Other
| Other | 1993 IEEE International Symposium on Circuits and Systems |
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| City | Chicago, IL, USA |
| Period | 5/3/93 → 5/6/93 |