An Empirical Study of Periodic Noise Filtering in Fourier Domain: an Introduction to Novel Autonomous Periodic Noise Removal Algorithms - Atul Rai - Livros - LAP LAMBERT Academic Publishing - 9783659389948 - 2 de maio de 2013
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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

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An Empirical Study of Periodic Noise Filtering in Fourier Domain: an Introduction to Novel Autonomous Periodic Noise Removal Algorithms

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.

Mídia Livros     Paperback Book   (Livro de capa flexível e brochura)
Lançado 2 de maio de 2013
ISBN13 9783659389948
Editoras LAP LAMBERT Academic Publishing
Páginas 84
Dimensões 150 × 5 × 226 mm   ·   143 g
Idioma German  

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