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An Empirical Study of Periodic Noise Filtering in Fourier Domain: an Introduction to Novel Autonomous Periodic Noise Removal Algorithms Atul Rai
An Empirical Study of Periodic Noise Filtering in Fourier Domain: an Introduction to Novel Autonomous Periodic Noise Removal Algorithms
Atul Rai
Quasi periodic noise or moiré 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.
| Medios de comunicación | Libros Paperback Book (Libro con tapa blanda y lomo encolado) |
| Publicado | 2 de mayo de 2013 |
| ISBN13 | 9783659389948 |
| Editores | LAP LAMBERT Academic Publishing |
| Páginas | 84 |
| Dimensiones | 150 × 5 × 226 mm · 143 g |
| Lengua | Alemán |
Ver todo de Atul Rai ( Ej. Paperback Book )