Cramer-Rao bound analysis of multi-frame blind deconvolution
نویسنده
چکیده
OF THESIS Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science Optical Science and Engineering The University of New Mexico Albuquerque, New Mexico May, 2007
منابع مشابه
Improved Cramer-Rao Inequality for Randomly Censored Data
As an application of the improved Cauchy-Schwartz inequality due to Walker (Statist. Probab. Lett. (2017) 122:86-90), we obtain an improved version of the Cramer-Rao inequality for randomly censored data derived by Abdushukurov and Kim (J. Soviet. Math. (1987) pp. 2171-2185). We derive a lower bound of Bhattacharya type for the mean square error of a parametric function based on randomly censor...
متن کاملCramer-Rao bounds for blind multichannel estimation
Certain blind channel estimation techniques allow the identification of the channel up to a scale or phase factor. This results in singularity of the Fisher Information Matrix (FIM). The Cramér–Rao Bound, which is the inverse of the FIM, is then not defined. To regularize the estimation problem, one can impose constraints on the parameters. In general, many sets of constraints are possible but ...
متن کاملNoise Reduction in support-constrained multi-frame blind-deconvolution restorations as a function of the number of data frames and the support constraint sizes (Preprint)
We show that the amount of relative noise reduction in multi-frame blind deconvolution image restorations is greatest for just a few data frames and is a more complicated function of the support constraint sizes. ©2007 Optical Society of America OCIS codes: (100.3020) Image reconstruction-restoration; (100.2980) Image enhancement
متن کاملتخمین جهت منابع با استفاده از زیرفضای کرونکر
This paper proceeds directions of arrival (DOA) estimation by a linear array. These years, some algorithms, e.g. Khatri-Rao approach, Nested array, Dynamic array have been proposed for estimating more DOAs than sensors. These algorithms can merely estimate uncorrelated sources. For Khatri-Rao approach, this is due to the fact that Khatri-Rao product discard the non-diagonal entries of the corre...
متن کاملBayesian Cramér-Rao Bound for Noisy Non-Blind and Blind Compressed Sensing
In this paper, we address the theoretical limitations in reconstructing sparse signals (in a known complete basis) using compressed sensing framework. We also divide the CS to non-blind and blind cases. Then, we compute the Bayesian Cramer-Rao bound for estimating the sparse coefficients while the measurement matrix elements are independent zero mean random variables. Simulation results show a ...
متن کامل