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Image denoising has been a well-studied problem and a highly demanded area of research in the field of image processing. Images are generally degraded due to the faulty sensor, channel error, camera miss-focus, atmospheric turbulence, relative camera motion, image acquisition and or transmission etc. Such conditions are inevitable while capturing a scene through a camera. As degraded images are of little scientific values, restorations of such images are utmost essential. As camera manufacturers continue to pack increasing numbers of pixels per unit area, an increase in noise sensitivity…mehr

Produktbeschreibung
Image denoising has been a well-studied problem and a highly demanded area of research in the field of image processing. Images are generally degraded due to the faulty sensor, channel error, camera miss-focus, atmospheric turbulence, relative camera motion, image acquisition and or transmission etc. Such conditions are inevitable while capturing a scene through a camera. As degraded images are of little scientific values, restorations of such images are utmost essential. As camera manufacturers continue to pack increasing numbers of pixels per unit area, an increase in noise sensitivity manifests itself in the form of a noisier image. Researchers continue to focus attention on it to better the current state-of-the-art. Recently proposed methods take different approaches to the problem and yet their denoising performances are comparable. Impulsive noise is common in images, which arise at the time of image acquisition and or transmission of images. This book discusses various types of noises which affect digital images and also proposed many algorithms for removal of impulse noise from images.
Autorenporträt
Dr. Punyaban Patel is a Professor in Computer Science and Engineering at Malla Reddy Institute of Technology affiliated to JNTU Hyderabad, India. He has published more than 55 research papers in national/international conferences and journals, including book chapters. His research interest is image processing, sensor networks, and cloud computing.