Nonlinear image restoration

Ungan, Cahit Uğur
This thesis analyzes the process of deblurring of degraded images generated by space-variant nonlinear image systems with Gaussian observation noise. The restoration of blurred images is performed by using two methods; a modified version of the Optimum Decoding Based Smoothing Algorithm and the Bootstrap Filter Algorithm which is a version of Particle Filtering methods. A computer software called MATLAB is used for performing the simulations of image estimation. The results of some simulations for various observation and image models are presented.


Nonlinear estimation techniques applied to econometric problems
Aslan, Serdar; Demirbaş, Kerim; Department of Electrical and Electronics Engineering (2004)
This thesis considers the filtering and prediction problems of nonlinear noisy econometric systems. As a filter/predictor, the standard tool Extended Kalman Filter and new approaches Discrete Quantization Filter and Sequential Importance Resampling Filter are used. The algorithms are compared by using Monte Carlo Simulation technique. The advantages of the new algorithms over Extended Kalman Filter are shown.
Ofdm papr reduction with linear coding and codeword modification
Susar, Aylin; Tanık, Yalçın; Department of Electrical and Electronics Engineering (2005)
In this thesis, reduction of the Peak-to-Average Power Ratio (PAPR) of Orthogonal Frequency Division Multiplexing (OFDM) is studied. A new PAPR reduction method is proposed that is based on block coding the input data and modifying the codeword until the PAPR is reduced below a certain threshold. The method makes use of the error correction capability of the block code employed. The performance of the algorithm has been investigated through theoretical models and computer simulations. For performance evalua...
Signal reconstruction from nonuniform samples
Serdaroğlu, Bülent; Tuncer, Temel Engin; Department of Electrical and Electronics Engineering (2005)
Sampling and reconstruction is used as a fundamental signal processing operation since the history of signal theory. Classically uniform sampling is treated so that the resulting mathematics is simple. However there are various instances that nonuniform sampling and reconstruction of signals from their nonuniform samples are required. There exist two broad classes of reconstruction methods. They are the reconstruction according to a deterministic, and according to a stochastic model. In this thesis, the mos...
Nonuform pulse repetition interval optimization for pulse doppler radars
Mercan, Hasan; Tanık, Yalçın; Department of Electrical and Electronics Engineering (2004)
In this thesis, a method of optimization of nonuniform pulse repetition interval for pulse Doppler radars is investigated. PRI jittering technique is used for the selection of inter-pulse intervals. An environment with white Gaussian noise and clutter interference is defined and applying generalized likelihood ratio test, a sufficient statistic function for the detection of the target is derived. The effect of jitter set selection on range and Doppler ambiguity resolution and clutter rejection is investigat...
Direction finding for coherent, cyclostationary signals via a uniform circular array
Atalay Çetinkaya, Burcu; Koç, Arzu; Department of Electrical and Electronics Engineering (2009)
In this thesis work, Cyclic Root MUSIC method is integrated with spatial smoothing and interpolation techniques to estimate the direction of arrivals of coherent,cyclostationary signals received via a Uniform Circular Array (UCA). Cyclic Root MUSIC and Conventional Root MUSIC algorithms are compared for various signal scenarios by computer simulations. A cyclostationary process is a random process with probabilistic parameters, such as the autocorrelation function, that vary periodically with time. Most of ...
Citation Formats
C. U. Ungan, “Nonlinear image restoration,” M.S. - Master of Science, Middle East Technical University, 2005.