Image noise variance estimation using the mixed Lagrange time-delay autoregressive model.
The mixed Lagrange time-delay estimation autoregressive (MLTDEAR) model is proposed as a solution to estimate image noise variance. The only information available to the proposed estimator is a corrupted image and the nature of additive white noise. The image autocorrelation function is calculated and used to obtain the MLTDEAR model coefficients; the relationship between the MLTDEAR and linear prediction models is utilized to estimate the model coefficients. The forward-backward prediction is then used to obtain the predictor coefficients; the MLTDEAR model coefficients and prior samples of zero-offset autocorrelation values are next used to predict the power of the noise-free image. Furthermore, the fundamental performance limit of the signal and noise estimation, as derived from the Cramer-Rao inequality, is presented.
Sim
K-S
KS
Faculty of Engineering and Technology, Multimedia University, Melaka, Malaysia. sksbg2003@yahoo.com
Tso
C-P
CP
Law
K-K
KK
D007089:Image Enhancement; D007091:Image Processing, Computer-Assisted; D008855:Microscopy, Electron, Scanning / Q000379:methods*; D008954:Models, Biological; D012984:Software; D014934:Wood / Q000648:ultrastructure