Applications of Wavelet Transform in Registration, Segmentation, Denoising, and Compression of Medical Images View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2013

AUTHORS

Neelu Dubey , Meghna Jain , Mukta Bhatele

ABSTRACT

Wavelet transforms and other multiscale analysis functions have been used for compact signal and image representations in denoising, compression, and feature detection processing problems. The wavelet transform itself offers great design flexibility. Basis selection, spatial-frequency tiling, and various wavelet threshold strategies can be optimized for best adaptation to a processing application, data characteristics, and feature of interest. Fast implementation of wavelet transforms using a filter-bank framework enables real-time processing capability. Instead of trying to replace standard image processing techniques, wavelet transforms offer an efficient representation of the signal, finely tuned to its intrinsic properties. By combining such representations with simple processing techniques in the transform domain, multiscale analysis can accomplish remarkable performance and efficiency for many image processing problems. More... »

PAGES

117-130

Book

TITLE

Proceedings of All India Seminar on Biomedical Engineering 2012 (AISOBE 2012)

ISBN

978-81-322-0969-0
978-81-322-0970-6

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-81-322-0970-6_14

DOI

http://dx.doi.org/10.1007/978-81-322-0970-6_14

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1010376458


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