Modern image processing techniques are based on multiresolution geometrical methods of image representation. These methods are efficient in sparse approximation of digital images. There is a wide family of functions called simply ‘X-lets’, and these methods can be divided into two groups: the adaptive and the nonadaptive. This book is devoted to the adaptive methods of image approximation, especially to multismoothlets. Besides multismoothlets, several other new ideas are also covered. Current literature considers the black and white images with smooth horizon function as the model for sparse approximation but here, the class of blurred multihorizon is introduced, which is then used in the approximation of images with multiedges. Additionally, the semi-anisotropic model of multiedge representation, the introduction of the shift invariant multismoothlet transform and sliding multismoothlets are also covered. Geometrical Multiresolution Adaptive Transforms should be accessible to both mathematicians and computer scientists. It is suitable as a professional reference for students, researchers and engineers, containing many open problems and will be an excellent starting point for those who are beginning new research in the area or who want to use geometrical multiresolution adaptive methods in image processing, analysis or compression.
Modern image processing techniques are based on multiresolution geometrical methods of image representation. These methods are efficient in sparse approximation of digital images. There is a wide family of functions called simply ‘X-lets’, and these methods can be divided into two groups: the adaptive and the nonadaptive. This book is devoted to the adaptive methods of image approximation, especially to multismoothlets. Besides multismoothlets, several other new ideas are also covered. Current literature considers the black and white images with smooth horizon function as the model for sparse approximation but here, the class of blurred multihorizon is introduced, which is then used in the approximation of images with multiedges. Additionally, the semi-anisotropic model of multiedge representation, the introduction of the shift invariant multismoothlet transform and sliding multismoothlets are also covered. Geometrical Multiresolution Adaptive Transforms should be accessible to both mathematicians and computer scientists. It is suitable as a professional reference for students, researchers and engineers, containing many open problems and will be an excellent starting point for those who are beginning new research in the area or who want to use geometrical multiresolution adaptive methods in image processing, analysis or compression.
This book is the final product of the research project ``Populist political communication: political messages, media coverage and audience feedback''. It focuses on three categories of participants in populist political communication, that is political actors, media, and citizens. In particular, this study offers an insight into reasons behind the choice by Polish politicians and journalists to use populist messages, as well as factors fostering populist sentiments among Polish citizens. Its multi-dimensional approach utilizes communication, media and political science theories to make sense of production, dissemination, reception, and impact of populist political messages. This publication combines several aspects of research on populism. On the one hand, it is a continuation of theoretical and interpretative discussions present in both Polish and foreign literature. The correlation between Polish and foreign research is important, as it allows for comparison of the results obtained in different research contexts, as well as for further theoretical discussions on the methods of researching and describing the discussed phenomena. On the other hand, it attempts to capture a specificity of the Polish populist political communication in recent years (2015-2017).
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