Speckle noise reduction in SAS imagery
Signal Processing
Automatica (Journal of IFAC)
Speckle suppression in ultrasonic images based on undecimated wavelets
EURASIP Journal on Applied Signal Processing
Computational Statistics & Data Analysis
Finding out general tendencies in speckle noise reduction in ultrasound images
Expert Systems with Applications: An International Journal
Filtering in Generalized Signal-Dependent Noise Model Using Covariance Information
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Approximate maximum likelihood estimators for array processing inmultiplicative noise environments
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Multi-sensor optimal information fusion Kalman filter
Automatica (Journal of IFAC)
Mathematical and Computer Modelling: An International Journal
Optimal recursive estimation with uncertain observation
IEEE Transactions on Information Theory
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The problem of estimating a degraded image using observations acquired from multiple sensors is addressed when the image degradation is modelled by white multiplicative and additive noise. Assuming the state-space model is unknown, the centralized and distributed filtering algorithms are derived using the information provided by the covariance functions of the processes involved in the measurement equation. The filters obtained are applied to an image affected by multiplicative and additive noise, and the goodness of the centralized and distributed filters is compared by examining the respective filtering error variances.