An Empirical Study of Periodic Noise Filtering in Fourier Domain
Paperback. 84 pages. Dimensions: 8.7in. x 5.9in. x 0.2in.Quasi periodic noise or moir patterns are one of the complex noise models that are responsible for the various errors in X-ray imaging and in other image transmission applications. This book demonstrates an empirical study of various linear and non linear notch filters in Fourier domain. The book also explores a novel machine learning (Bagging) based periodic noise removal technique. The method can be used as an automated techniques to highlight and remove the periodic and quasi periodic noise from an image. A part of this book is dedicated to the design and implementation of image filtering tool in Fourier domain on Matlab platform. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Bookseller Inventory # 9783659389948
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About the Author: Atul Rai completed his under graduation in Computer Science from India, He pursued his MS in Artificial Intelligence from University of Manchester UK. Currently, he is working as Research Associate in Department of Image Processing and Computer Graphics, University of Szeged, Hungary.His field of interest is Computer vision & Machine Learning.
Title: An Empirical Study of Periodic Noise ...
Publisher: LAP LAMBERT Academic Publishing
Book Condition: New
Book Type: Paperback
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