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bispectrum
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Center of confusion estimation for out-of-focus images based on bispectrum
, Article International Conference on Computational Intelligence and Multimedia Applications, ICCIMA 2007, Sivakasi, Tamil Nadu, 13 December 2007 through 15 December 2007 ; Volume 3 , 2008 , Pages 501-506 ; 0769530508 (ISBN); 9780769530505 (ISBN) ; Darabi, A. A ; Jamzad, M ; Sharif University of Technology
2008
Abstract
In this paper a new method for out-of-focus blur estimation and restoration in presence of Gaussian noise is proposed. This method is based on Bispectrum transformation. It has been proved that functions with Gaussian distribution are suppressed in Bispectrum domain. The image blur criterion is estimated using information in image Bispectrum transformation. Then, an inverse filter is used for blurred image restoration. Experimental results show satisfactory performance of presented method in degradation function parameter estimation in comparison with other algorithms. This superiority is especially obvious in restoration of noisy images, since most of the methods do not take into account...
Application of Different Signal Processing in Rolling Element Bearing Fault Diagnosis
, M.Sc. Thesis Sharif University of Technology ; Behzad, Mehdi (Supervisor) ; Mehdigholi, Hamid (Supervisor)
Abstract
Rolling bearings are important parts in rotating machinery. Unsuitable practice of this bearing causes unsuitable output in this collection. In some machines like helicopters, sudden faults of this rolling bearing cause body dangers. According to this point, diagnose of bearing fault is an important case in condition monitoring domain. There are many ways for diagnose of fault in bearing which most of them are important subject in signal processing. In this project first of all, the most important and applicable signal processing methods, which are useful in diagnose of fault in bearings are introduced then three of these methods are chosen and applied on time signals of experimental...
Motion blur identification in noisy images using mathematical models and statistical measures
, Article Pattern Recognition ; Volume 40, Issue 7 , 2007 , Pages 1946-1957 ; 00313203 (ISSN) ; Jamzad, M ; Sharif University of Technology
2007
Abstract
Motion blur is one of the most common blurs that degrades images. Restoration of such images is highly dependent on estimation of motion blur parameters. Since 1976, many researchers have developed algorithms to estimate linear motion blur parameters. These algorithms are different in their performance, time complexity, precision and robustness in noisy environments. In this paper, we have presented a novel algorithm to estimate linear motion blur parameters such as direction and length. We used Radon transform to find direction and bispectrum modeling to find the length of motion. Our algorithm is based on the combination of spatial and frequency domain analysis. The great benefit of our...