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)|
|Number of pages||4|
|Journal||ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings|
|State||Published - 1985|
ASJC Scopus subject areas
- Signal Processing
- Electrical and Electronic Engineering