Geometrical Multiresolution Adaptive Transforms [electronic resource] : Theory and Applications / by Agnieszka Lisowska
- Lisowska, Agnieszka
- Cham : Springer International Publishing : Imprint: Springer, 2014.
- Physical Description:
- XII, 107 pages 65 illustrations, 21 illustrations in color : online resource
- Additional Creators:
- SpringerLink (Online service)
- Studies in Computational Intelligence, 1860-949X ; 545
- Introduction -- Smoothlets -- Multismoothlets -- Moments-Based Multismoothlet Transform -- Image Compression -- Image Denoising -- Edge Detection -- Summary.
- 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.
- Digital File Characteristics:
- text file PDF
- AVAILABLE ONLINE TO AUTHORIZED PSU USERS.
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