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Geometrical Multiresolution Adaptive Transforms Theory and Applications /
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:...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cham :
Springer International Publishing : Imprint: Springer,
2014.
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| Edición: | 1st ed. 2014. |
| Colección: | Studies in Computational Intelligence,
545 |
| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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| 001 | 978-3-319-05011-9 | ||
| 003 | DE-He213 | ||
| 005 | 20220117023556.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 140324s2014 sz | s |||| 0|eng d | ||
| 020 | |a 9783319050119 |9 978-3-319-05011-9 | ||
| 024 | 7 | |a 10.1007/978-3-319-05011-9 |2 doi | |
| 050 | 4 | |a TA1634 | |
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| 100 | 1 | |a Lisowska, Agnieszka. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Geometrical Multiresolution Adaptive Transforms |h [electronic resource] : |b Theory and Applications / |c by Agnieszka Lisowska. |
| 250 | |a 1st ed. 2014. | ||
| 264 | 1 | |a Cham : |b Springer International Publishing : |b Imprint: Springer, |c 2014. | |
| 300 | |a XII, 107 p. 65 illus., 21 illus. in color. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file |b PDF |2 rda | ||
| 490 | 1 | |a Studies in Computational Intelligence, |x 1860-9503 ; |v 545 | |
| 505 | 0 | |a Introduction -- Smoothlets -- Multismoothlets -- Moments-Based Multismoothlet Transform -- Image Compression -- Image Denoising -- Edge Detection -- Summary. | |
| 520 | |a 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. | ||
| 650 | 0 | |a Computer vision. | |
| 650 | 0 | |a Computer science-Mathematics. | |
| 650 | 1 | 4 | |a Computer Vision. |
| 650 | 2 | 4 | |a Mathematical Applications in Computer Science. |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9783319050126 |
| 776 | 0 | 8 | |i Printed edition: |z 9783319050102 |
| 776 | 0 | 8 | |i Printed edition: |z 9783319377148 |
| 830 | 0 | |a Studies in Computational Intelligence, |x 1860-9503 ; |v 545 | |
| 856 | 4 | 0 | |u https://doi.uam.elogim.com/10.1007/978-3-319-05011-9 |z Texto Completo |
| 912 | |a ZDB-2-ENG | ||
| 912 | |a ZDB-2-SXE | ||
| 950 | |a Engineering (SpringerNature-11647) | ||
| 950 | |a Engineering (R0) (SpringerNature-43712) | ||