An Empirical Study of Periodic noise filtering in Fourier domain - Rai, Atul
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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.…mehr

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Produktbeschreibung
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.
Autorenporträt
Le docteur Rai poursuit des études de maîtrise en chirurgie orale et maxillo-faciale et a présenté un certain nombre de posters et d'articles lors de conférences nationales et internationales ; il a également une expérience professionnelle de plus de cinq ans en tant que praticien privé. Il a suivi avec succès un cours d'implantologie dentaire et pratique régulièrement la réhabilitation complète de la bouche.