Title :
A robust method for parameter estimation of signal-dependent noise models in digital images
Author :
Aiazzi, B. ; Alparone, L. ; Baronti, S.
Author_Institution :
CNR, Firenze, Italy
Abstract :
A class of signal-dependent noise models is discussed, with reference to the cases of film-grain and speckle noise, which are commonly encountered in image processing applications. The model is uniquely defined by the variance of the zero-mean random noise (independent of the signal) and by the gamma exponent which rules the dependence with the signal. A robust procedure for measuring such parameters directly from the noisy images is presented. First, the gamma coefficient is estimated from at least three homogeneous non-textured regions. Then, the noise variance is determined as the mode of the histogram of the ratio between the local variance, and the local mean raised to twice the gamma. Computer simulations show the high accuracy of the results
Keywords :
adaptive filters; adaptive signal processing; filtering theory; image processing; least mean squares methods; parameter estimation; random noise; speckle; statistical analysis; accuracy; adaptive filtering; computer simulations; digital images; film-grain; gamma coefficient; gamma exponent; histogram; homogeneous nontextured regions; image processing applications; local linear minimum MSE filter; local mean; local variance; noisy images; parameter estimation; parameters measurement; ratio; robust method; signal-dependent noise models; speckle noise; zero-mean random noise variance; Additive noise; Digital images; Noise level; Noise reduction; Noise robustness; Optical films; Optical filters; Optical noise; Parameter estimation; Signal processing;
Conference_Titel :
Digital Signal Processing Proceedings, 1997. DSP 97., 1997 13th International Conference on
Conference_Location :
Santorini
Print_ISBN :
0-7803-4137-6
DOI :
10.1109/ICDSP.1997.628421