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  • Broschiertes Buch

In this book we propose the following algorithms and applications for image processing: 1) The increasing use of Web development and transmission networks tools last decades has lead to huge 2D databases that still have to be correctly indexed. The context of this book is the content-based image retrieval (CBIR) and its application in lifelogging; 2) In the context of the frequency estimation, the new 3D high resolution spectral analysis method is presented using second order statistics and higher order statistics. The application of the frequency content in the field of CBIR allows developing…mehr

Produktbeschreibung
In this book we propose the following algorithms and applications for image processing: 1) The increasing use of Web development and transmission networks tools last decades has lead to huge 2D databases that still have to be correctly indexed. The context of this book is the content-based image retrieval (CBIR) and its application in lifelogging; 2) In the context of the frequency estimation, the new 3D high resolution spectral analysis method is presented using second order statistics and higher order statistics. The application of the frequency content in the field of CBIR allows developing of new descriptor vector witch characterizes the image. The filtering of seismic images using their content frequency is a new approach allows improving the quality of images; 3) We consider the class of subgradient methods for solving minimization of a non-smooth convex function regularized by the discretized L1 norm models arising in image processing. In last chapter we propose a fast control subgradient algorithm for image regularization.
Autorenporträt
Abdelkrim El Mouatasim, born in 1973, received a Ph.D. degree in applied mathematics and scientific computation in 2007 from Mohammadia Engineering School in Rabat. Currently he works for the Department of Mathematics at the Faculty of Ouarzazate FPO, Ibn Zohr University, Morocco. His research interests include global optimization modelling.