Lower bound on average mean-square error for image restoration
- 1 January 1991
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Signal Processing
- Vol. 39 (2) , 497-499
- https://doi.org/10.1109/78.80837
Abstract
An average mean-square error bound that is applicable to general image observation models involving degradations of blur, signal-dependent and signal-independent noise, and sensor nonlinearity is derived. A Cramer-Rao lower bound on average mean-square errors for any unbiased image restoration scheme is derived. This bound is analytically expressed as a function of degradation parameters of imaging systems. Potential performance improvements by incorporating signal-dependent noise or sensor nonlinearity into algorithmic design are discussedKeywords
This publication has 1 reference indexed in Scilit:
- Optimal estimation in signal-dependent noiseJournal of the Optical Society of America, 1978