digital image processing practical di sarode milindkumar (10 risultati)

Condizione: New.

Condizione: New.

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Taschenbuch. Condizione: Neu. Digital Image Processing: A Practical approach for Image Restoration | Image Enhancement | Milindkumar Sarode | Taschenbuch | Englisch | 2020 | LAP LAMBERT Academic Publishing | EAN 9786202557665 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Various filtering algorithms have been discussed in this book to suppress not only Gaussian noise, Impulse noise and Mixture of Gaussian and Impulse noise, but also Rician and Impulse noise. The filter performance is compared with existing filters in terms of Peak-Signal-to-Noise ratio (PSNR) and visual quality of restored images. The entire discussion is focused on developing an efficient image denoising filters such as Universal noise removal algorithm, Edge Preservation and Removal of Cracks and noise, Rician and Gaussian noise reduction in 3-D MRI, Rician and Speckle noise reduction in Ultrasound images, Total Variation Restoration algorithm, Restoration of images due to Camera Motion blur, Fusion and Denoising of more than two Multifocus images, Motion Compensation in MRI, 3-D Reconstruction of coronary arteries, Fuzzy System for Color image enhancement, Adaptive Bilateral Filter for sharpness, enhancement and noise removal, and Restoration of Video sequences. The performance of the filters are tested in terms of Peak-Signal-to-noise ratio (PSNR), Signal-to noise ratio (SNR), Mean absolute differences (MAE), Root mean square error (RMSE) and visual quality of restored images. 264 pp. Englisch.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Sarode Dr. MilindkumarA diligent professional and a perfectionist having 20 years of academic experience, with JDIET, Yavatmal, Sipna COET, Amravati and JCOET as a Professor and Head of Computer Engineering Department 4.9 years Ma.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Various filtering algorithms have been discussed in this book to suppress not only Gaussian noise, Impulse noise and Mixture of Gaussian and Impulse noise, but also Rician and Impulse noise. The filter performance is compared with existing filters in terms of Peak-Signal-to-Noise ratio (PSNR) and visual quality of restored images. The entire discussion is focused on developing an efficient image denoising filters such as Universal noise removal algorithm, Edge Preservation and Removal of Cracks and noise, Rician and Gaussian noise reduction in 3-D MRI, Rician and Speckle noise reduction in Ultrasound images, Total Variation Restoration algorithm, Restoration of images due to Camera Motion blur, Fusion and Denoising of more than two Multifocus images, Motion Compensation in MRI, 3-D Reconstruction of coronary arteries, Fuzzy System for Color image enhancement, Adaptive Bilateral Filter for sharpness, enhancement and noise removal, and Restoration of Video sequences. The performance of the filters are tested in terms of Peak-Signal-to-noise ratio (PSNR), Signal-to noise ratio (SNR), Mean absolute differences (MAE), Root mean square error (RMSE) and visual quality of restored images.Books on Demand GmbH, Überseering 33, 22297 Hamburg 264 pp. Englisch.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Various filtering algorithms have been discussed in this book to suppress not only Gaussian noise, Impulse noise and Mixture of Gaussian and Impulse noise, but also Rician and Impulse noise. The filter performance is compared with existing filters in terms of Peak-Signal-to-Noise ratio (PSNR) and visual quality of restored images. The entire discussion is focused on developing an efficient image denoising filters such as Universal noise removal algorithm, Edge Preservation and Removal of Cracks and noise, Rician and Gaussian noise reduction in 3-D MRI, Rician and Speckle noise reduction in Ultrasound images, Total Variation Restoration algorithm, Restoration of images due to Camera Motion blur, Fusion and Denoising of more than two Multifocus images, Motion Compensation in MRI, 3-D Reconstruction of coronary arteries, Fuzzy System for Color image enhancement, Adaptive Bilateral Filter for sharpness, enhancement and noise removal, and Restoration of Video sequences. The performance of the filters are tested in terms of Peak-Signal-to-noise ratio (PSNR), Signal-to noise ratio (SNR), Mean absolute differences (MAE), Root mean square error (RMSE) and visual quality of restored images.