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Sinopsis
This work is motivated by the potential and promise of image fusion technologies in the multi-sensor image fusion system. The aim of this research is to focus on multi-sensor pixel level image fusion for medical application due to its significance of medical field. Medical fusion methods are only a possible way that able to combine correlating information of multiple images into a single image to explore the possibility of data reduction and improvement of information density. The dissertation explores the possibility of using Stationary Wavelet approach in image fusion and further optimization using Genetic Algorithm and Particle Swarm Optimization. The comparative analysis of Stationary wavelet transform combined with optimization algorithm has been performed with several sets of computed Tomography (CT) scan and Magnetic Resonance imaging (MRI) images using MATLAB. Improve statistics results are obtained in terms of peak signal to noise ratio (PSNR), entropy, root mean square error (RMSE), edge strength, mutual information.
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Reseña del editor
This work is motivated by the potential and promise of image fusion technologies in the multi-sensor image fusion system. The aim of this research is to focus on multi-sensor pixel level image fusion for medical application due to its significance of medical field. Medical fusion methods are only a possible way that able to combine correlating information of multiple images into a single image to explore the possibility of data reduction and improvement of information density. The dissertation explores the possibility of using Stationary Wavelet approach in image fusion and further optimization using Genetic Algorithm and Particle Swarm Optimization. The comparative analysis of Stationary wavelet transform combined with optimization algorithm has been performed with several sets of computed Tomography (CT) scan and Magnetic Resonance imaging (MRI) images using MATLAB. Improve statistics results are obtained in terms of peak signal to noise ratio (PSNR), entropy, root mean square error (RMSE), edge strength, mutual information.
Biografía del autor
Dr. Reecha Sharma had her Ph.D in Image Processing. She is having ten years of teaching experience. At present she is working as Assistant Professor in Department of ECE, Punjabi University Patiala, India. She has more than 40 papers in International Journals and International Conferences. She had guided 17 M.tech students.
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Medical Image Fusion Based On SWT and Optimization With GA And PSO
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LAP Lambert Academic Publishing Okt 2016, 2016
ISBN 10: 3659959081
ISBN 13: 9783659959080
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This work is motivated by the potential and promise of image fusion technologies in the multi-sensor image fusion system. The aim of this research is to focus on multi-sensor pixel level image fusion for medical application due to its significance of medical field. Medical fusion methods are only a possible way that able to combine correlating information of multiple images into a single image to explore the possibility of data reduction and improvement of information density. The dissertation explores the possibility of using Stationary Wavelet approach in image fusion and further optimization using Genetic Algorithm and Particle Swarm Optimization. The comparative analysis of Stationary wavelet transform combined with optimization algorithm has been performed with several sets of computed Tomography (CT) scan and Magnetic Resonance imaging (MRI) images using MATLAB. Improve statistics results are obtained in terms of peak signal to noise ratio (PSNR), entropy, root mean square error (RMSE), edge strength, mutual information. 88 pp. Englisch. Nº de ref. del artículo: 9783659959080
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Medical Image Fusion Based On SWT and Optimization With GA And PSO
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LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659959081
ISBN 13: 9783659959080
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This work is motivated by the potential and promise of image fusion technologies in the multi-sensor image fusion system. The aim of this research is to focus on multi-sensor pixel level image fusion for medical application due to its significance of medical field. Medical fusion methods are only a possible way that able to combine correlating information of multiple images into a single image to explore the possibility of data reduction and improvement of information density. The dissertation explores the possibility of using Stationary Wavelet approach in image fusion and further optimization using Genetic Algorithm and Particle Swarm Optimization. The comparative analysis of Stationary wavelet transform combined with optimization algorithm has been performed with several sets of computed Tomography (CT) scan and Magnetic Resonance imaging (MRI) images using MATLAB. Improve statistics results are obtained in terms of peak signal to noise ratio (PSNR), entropy, root mean square error (RMSE), edge strength, mutual information. Nº de ref. del artículo: 9783659959080
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Medical Image Fusion Based On SWT and Optimization With GA And PSO
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LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659959081
ISBN 13: 9783659959080
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Librería: moluna, Greven, Alemania
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Sharma ReechaDr. Reecha Sharma had her Ph.D in Image Processing. She is having ten years of teaching experience. At present she is working as Assistant Professor in Department of ECE, Punjabi University Patiala, India. She has more t. Nº de ref. del artículo: 159148421
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Medical Image Fusion Based On SWT and Optimization With GA And PSO
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LAP LAMBERT Academic Publishing, 2016
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Paperback. Condición: Brand New. 88 pages. 8.66x5.91x0.20 inches. In Stock. Nº de ref. del artículo: __3659959081
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Medical Image Fusion Based On SWT and Optimization With GA And PSO
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LAP LAMBERT Academic Publishing Okt 2016, 2016
ISBN 10: 3659959081
ISBN 13: 9783659959080
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This work is motivated by the potential and promise of image fusion technologies in the multi-sensor image fusion system. The aim of this research is to focus on multi-sensor pixel level image fusion for medical application due to its significance of medical field. Medical fusion methods are only a possible way that able to combine correlating information of multiple images into a single image to explore the possibility of data reduction and improvement of information density. The dissertation explores the possibility of using Stationary Wavelet approach in image fusion and further optimization using Genetic Algorithm and Particle Swarm Optimization. The comparative analysis of Stationary wavelet transform combined with optimization algorithm has been performed with several sets of computed Tomography (CT) scan and Magnetic Resonance imaging (MRI) images using MATLAB. Improve statistics results are obtained in terms of peak signal to noise ratio (PSNR), entropy, root mean square error (RMSE), edge strength, mutual information.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 88 pp. Englisch. Nº de ref. del artículo: 9783659959080
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Medical Image Fusion Based On SWT and Optimization With GA And PSO
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ISBN 10: 3659959081
ISBN 13: 9783659959080
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Taschenbuch. Condición: Neu. Medical Image Fusion Based On SWT and Optimization With GA And PSO | Reecha Sharma | Taschenbuch | 88 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659959080 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Nº de ref. del artículo: 107570366
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