Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği

Permanent URI for this collectionhttps://hdl.handle.net/11147/11

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Author: search.filters.author.Kuruoğlu, Ercan E.COAR Access Rights: search.filters.coarAccessRights.open access

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  • Article
    Citation - WoS: 18
    Citation - Scopus: 19
    Generalized Bayesian Model Selection for Speckle on Remote Sensing Images
    (Institute of Electrical and Electronics Engineers Inc., 2019) Karakuş, Oktay; Kuruoğlu, Ercan E.; Altınkaya, Mustafa Aziz
    Synthetic aperture radar (SAR) and ultrasound (US) are two important active imaging techniques for remote sensing, both of which are subject to speckle noise caused by coherent summation of back-scattered waves and subsequent nonlinear envelope transformations. Estimating the characteristics of this multiplicative noise is crucial to develop denoising methods and to improve statistical inference from remote sensing images. In this paper, reversible jump Markov chain Monte Carlo (RJMCMC) algorithm has been used with a wider interpretation and a recently proposed RJMCMC-based Bayesian approach, trans-space RJMCMC, has been utilized. The proposed method provides an automatic model class selection mechanism for remote sensing images of SAR and US where the model class space consists of popular envelope distribution families. The proposed method estimates the correct distribution family, as well as the shape and the scale parameters, avoiding performing an exhaustive search. For the experimental analysis, different SAR images of urban, forest and agricultural scenes, and two different US images of a human heart have been used. Simulation results show the efficiency of the proposed method in finding statistical models for speckle.
  • Article
    Citation - WoS: 22
    Citation - Scopus: 27
    Modelling Impulsive Noise in Indoor Powerline Communication Systems
    (Springer Verlag, 2020) Karakuş, Oktay; Kuruoğlu, Ercan E.; Altınkaya, Mustafa Aziz
    Powerline communication (PLC) is an emerging technology that has an important role in smart grid systems. Due to making use of existing transmission lines for communication purposes, PLC systems are subject to various noise effects. Among those, the most challenging one is the impulsive noise compared to the background and narrowband noise. In this paper, we present a comparative study on modelling the impulsive noise amplitude in indoor PLC systems by utilising several impulsive distributions. In particular, as candidate distributions, we use the symmetric alpha-Stable (S alpha S), generalised Gaussian, Bernoulli Gaussian and Student's t distribution families as well as the Middleton Class A distribution, which dominates the literature as the impulsive noise model for PLC systems. Real indoor PLC system noise measurements are investigated for the simulation studies, which show that the S alpha S distribution achieves the best modelling success when compared to the other families in terms of the statistical error criteria, especially for the tail characteristics of the measured data sets.