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Article
Restoration of Noisy Blurred Images Using MFPIA and Discrete Wavelet Transform
استرجاع الصور المضببة ذات الضوضاء باستخدام الخوارزمية المطورة للخوارزمية التكرارية ثابتة الطور للصور المضببة و تحويلة المويجة المتقطعة

Author: Dunia S. Tahir دنيا ستار طاهر
Journal: Iraqi Journal for Electrical And Electronic Engineering المجلة العراقية للهندسة الكهربائية والالكترونية ISSN: 18145892 Year: 2013 Volume: 9 Issue: 1 Pages: 1-15
Publisher: Basrah University جامعة البصرة

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Abstract

In this paper, image deblurring and denoising are presented. The used images were blurred either with Gaussian or motion blur and corrupted either by Gaussian noise or by salt & pepper noise. In our algorithm, the modified fixed-phase iterative algorithm (MFPIA) is used to reduce the blur. Then a discrete wavelet transform is used to divide the image into two parts. The first part represents the approximation coefficients. While the second part represents the detail coefficients, that a noise is removed by using the BayesShrink wavelet thresholding method.

في هاا البث ,قدمت طرق إزالة التضبب و الض وضاء من الصور. جميع الصور المستخدمة مضببة إما ب (Gaussian) أو ب(Motion) و كان نوع الضوضاء إما (Gaussian noise) أو (Salt & pepper noise) .في خوارزميتنا, استخدمت الخوارزميةالمطورة للخوارزمية التكرارية ثابتة الطور للص ور المضببة لتقلل التضبب بينما استخدمت تحويلة المويجة المتقطعة لتقسيم الصورة إلى جزئيين. الجزءالأول يمثل معاملات التقريب. بينا الجزء الثاني و الاي يمثل معاملات التفاصيل سوف يقلل هاا الجزء الضوضاء بالاعتماد على طريقةBayesShrink wavelet thresholding


Article
Analysis of Scalability and Sensitivity for Chaotic Sine Cosine Algorithms

Authors: Ramzy S. Ali --- Dunia S. Tahir
Journal: Iraqi Journal for Electrical And Electronic Engineering المجلة العراقية للهندسة الكهربائية والالكترونية ISSN: 18145892 Year: 2018 Volume: 14 Issue: 2 Pages: 139-154
Publisher: Basrah University جامعة البصرة

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Abstract

Chaotic Sine-Cosine Algorithms (CSCAs) are new metaheuristic optimization algorithms. However, Chaotic Sine-Cosine Algorithm (CSCAs) are able to manipulate the problems in the standard Sine-Cosine Algorithm (SCA) like, slow convergence rate and falling into local solutions. This manipulation is done by changing the random parameters in the standard Sine-Cosine Algorithm (SCA) with the chaotic sequences. To verify the ability of the Chaotic Sine-Cosine Algorithms (CSCAs) for solving problems with large scale problems. The behaviors of the Chaotic Sine-Cosine Algorithms (CSCAs) were studied under different dimensions 10, 30, 100, and 200. The results show the high quality solutions and the superiority of all Chaotic Sine-Cosine Algorithms (CSCAs) on the standard SCA algorithm for all selecting dimensions. Additionally, different initial values of the chaotic maps are used to study the sensitivity of Chaotic Sine-Cosine Algorithms (CSCAs). The sensitivity test reveals that the initial value 0.7 is the best option for all Chaotic Sine-Cosine Algorithms (CSCAs).


Article
Restoration of Noisy Blurred Images

Authors: Fadhil A.Ali --- Dunia S.Tahir --- Jassim M.
Journal: Basrah Journal for Engineering Science مجلة البصرة للعلوم الهندسية ISSN: Print: 18146120; Online: 23118385 Year: 2010 Volume: 10 Issue: 2 Pages: 90-101
Publisher: Basrah University جامعة البصرة

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Abstract

in this paper, image deblurring and denoising are presented. The used images were blurred either with Gaussian or motion blur and corrupted either by Gaussian noise or by salt & pepper noise. In our algorithm, a discrete wavelet transform is used to divide the image into two parts. This partition will help in increasing the manipulation speed of images that are of the big sizes. Therefore, the first part represents the approximation coefficients, that a blur is reduced by using the modified fixed-phase iterative algorithm. While the second part represents the detail coefficients, that a noise is removed by using the BayesShrink wavelet thresholding method.

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Article
A Chaotic Crow Search Algorithm for High-Dimensional Optimization Problems

Authors: Dunia S. Tahir ديا ستار طاهر --- Ramzy S. Ali رمزي سالم عبي
Journal: Basrah Journal for Engineering Science مجلة البصرة للعلوم الهندسية ISSN: Print: 18146120; Online: 23118385 Year: 2017 Volume: 17 Issue: 1 Pages: 16-25
Publisher: Basrah University جامعة البصرة

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Abstract

Crow Search Algorithm is an innovative metaheuristic optimization algorithm. In this paper, chaotic mapsare combined into Crow Search Algorithm to increase itsglobal optimization. Ten variant chaotic maps are used and theTent map is found as the best choices for high dimensionalproblems. The novel Chaotic Crow Search Algorithm is reliedon the substitution of a random location of search space andthe awareness parameter of crow with chaotic sequences. Theresults show that the chaotic maps are able to enhance theperformance of the Crow Search Algorithm. Also the novelChaotic Crow Search Algorithm outperforms the conventionalCrow Search Algorithm, the first version of Chaotic Crow SearchThe algorithm, Genetic Algorithm, and Particle SwarmOptimization Algorithm from the point of view of the speedconvergence and the function dimensions

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