Abstract
A general formulation of constrained iterative restoration algorithms is introduced in which deterministic and/or statistical information about the undistorted signal and statistical information about the noises are directly incorporated into the iterative procedure. This a priori information is incorporated into the restoration algorithm by what is called 'soft' or statistical constraints. Their effect on the solution depends on the amount of noise on the data; that is, the constraint operator is 'turned off' for noiseless data. The development of the new iterative algorithm is based on results from regularization techniques for stabilizing ill-posed problems.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 700-703 |
| Number of pages | 4 |
| Journal | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
| State | Published - 1985 |
ASJC Scopus subject areas
- Software
- Signal Processing
- Electrical and Electronic Engineering