1 November 1992 Fractional Brownian motion: a maximum-likelihood estimator for blurred data
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Proceedings Volume 1818, Visual Communications and Image Processing '92; (1992) https://doi.org/10.1117/12.131508
Event: Applications in Optical Science and Engineering, 1992, Boston, MA, United States
Abstract
Fractional Brownian motion is a useful tool to describe many objects and phenomena. But in the case of real data, the estimation of the H parameter is corrupted by noise and sometimes blur. The maximum likelihood estimation of H can take into account these perturbations. This communication deals with the problem of the blur which is modeled by a low pass filter. It is then possible to rewrite the autocorrelation function of the data and the estimation of H is performed. The Cramer-Rao lower bound (CRLB) is stated. Finally, synthetic data permit the proof that the estimation of H is possible even if the signal is blurred. The variance of the estimates is compared with the CRLB and shows the quality of the results.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Rachid Harba, Rachid Harba, William J. Ohley, William J. Ohley, Stephan Hoefer, Stephan Hoefer, } "Fractional Brownian motion: a maximum-likelihood estimator for blurred data", Proc. SPIE 1818, Visual Communications and Image Processing '92, (1 November 1992); doi: 10.1117/12.131508; https://doi.org/10.1117/12.131508
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