Efficient Algorithms for Discrete Wavelet Transform - With Applications to Denoising and Fuzzy Inference Systems (Paperback, 2013 ed.)

Due to its inherent time-scale locality characteristics, the discrete wavelet transform (DWT) has received considerable attention in signal/image processing. Wavelet transforms have excellent energy compaction characteristics and can provide perfect reconstruction. The shifting (translation) and scaling (dilation) are unique to wavelets. Orthogonality of wavelets with respect to dilations leads to multigrid representation. As the computation of DWT involves filtering, an efficient filtering process is essential in DWT hardware implementation. In the multistage DWT, coefficients are calculated recursively, and in addition to the wavelet decomposition stage, extra space is required to store the intermediate coefficients. Hence, the overall performance depends significantly on the precision of the intermediate DWT coefficients. This work presents new implementation techniques of DWT, that are efficient in terms of computation, storage, and with better signal-to-noise ratio in the reconstructed signal.

General

Imprint:	Springer London
Country of origin:	United Kingdom
Series:	SpringerBriefs in Computer Science
Release date:	February 2013
First published:	2013
Authors:	K.K. Shukla • Arvind K. Tiwari
Dimensions:	235 x 155 x 7mm (L x W x T)
Format:	Paperback
Pages:	91
Edition:	2013 ed.
ISBN-13:	978-1-4471-4940-8
Categories:	Books > Computing & IT > General theory of computing > Data structures Books > Computing & IT > Computer programming > Algorithms & procedures Books > Computing & IT > Applications of computing > Image processing > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics > General
LSN:	1-4471-4940-8
Barcode:	9781447149408

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