Quality assurance is probably the most common and most studied problem in image processing. The image is assumed to be corrupted by impulse noise. In this book, want to estimate the noise in a singly image is estimated using the PCA algorithm. The image is divided into segment and noise is estimated through Principal component analysis (PCA). Contour based approach is used for the segmentation of image. A model is proposed which is used it to estimate noise standard deviation in noisy image. The RGB model will be used for noise estimation from an image. The noise is removed through principal component analysis with contour-based segmentation. It provide the efficiency for estimate and removal of noise. This book provides an efficient segmentation technique for segmenting color images. It provides a good compromise between the accuracy and the execution time: it is much faster than the methods and considerably more accurate than the methods. The proposed quality assurance method can be efficiently used in various image applications such as digital cameras and is superior because of its performance and simplicity.
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Sharma SmitaDr.Smita Sharma is currently working as an Associate Professor in AIML & Cyber Security Department of the Sagar Institute of Research & Technology, Bhopal.Her areas of interest include cyber security, digital forensics.Dr. Nº de ref. del artículo: 1702233171
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Taschenbuch. Condición: Neu. Neuware -Quality assurance is probably the most common and most studied problem in image processing. The image is assumed to be corrupted by impulse noise. In this book, want to estimate the noise in a singly image is estimated using the PCA algorithm. The image is divided into segment and noise is estimated through Principal component analysis (PCA). Contour based approach is used for the segmentation of image. A model is proposed which is used it to estimate noise standard deviation in noisy image. The RGB model will be used for noise estimation from an image. The noise is removed through principal component analysis with contour-based segmentation. It provide the efficiency for estimate and removal of noise. This book provides an efficient segmentation technique for segmenting color images. It provides a good compromise between the accuracy and the execution time: it is much faster than the methods and considerably more accurate than the methods. The proposed quality assurance method can be efficiently used in various image applications such as digital cameras and is superior because of its performance and simplicity.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 92 pp. Englisch. Nº de ref. del artículo: 9786206772217
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Quality assurance is probably the most common and most studied problem in image processing. The image is assumed to be corrupted by impulse noise. In this book, want to estimate the noise in a singly image is estimated using the PCA algorithm. The image is divided into segment and noise is estimated through Principal component analysis (PCA). Contour based approach is used for the segmentation of image. A model is proposed which is used it to estimate noise standard deviation in noisy image. The RGB model will be used for noise estimation from an image. The noise is removed through principal component analysis with contour-based segmentation. It provide the efficiency for estimate and removal of noise. This book provides an efficient segmentation technique for segmenting color images. It provides a good compromise between the accuracy and the execution time: it is much faster than the methods and considerably more accurate than the methods. The proposed quality assurance method can be efficiently used in various image applications such as digital cameras and is superior because of its performance and simplicity. Nº de ref. del artículo: 9786206772217
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