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Titlebook: Efficient Algorithms for Discrete Wavelet Transform; With Applications to K. K. Shukla,Arvind K. Tiwari Book 2013 The Editor(s) (if applica

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书目名称Efficient Algorithms for Discrete Wavelet Transform
副标题With Applications to
编辑K. K. Shukla,Arvind K. Tiwari
视频video
概述Describes a mathematical model to predict the errors introduced in the implementation of the discrete wavelet transform (DWT) on fixed-point processors.Explores the application of DWT on benchmark sig
丛书名称SpringerBriefs in Computer Science
图书封面Titlebook: Efficient Algorithms for Discrete Wavelet Transform; With Applications to K. K. Shukla,Arvind K. Tiwari Book 2013 The Editor(s) (if applica
描述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.
出版日期Book 2013
关键词Discrete Wavelet Transform; Efficient Algorithms; Error Analysis; Fuzzy Expert Systems; Image Processing
版次1
doihttps://doi.org/10.1007/978-1-4471-4941-5
isbn_softcover978-1-4471-4940-8
isbn_ebook978-1-4471-4941-5Series ISSN 2191-5768 Series E-ISSN 2191-5776
issn_series 2191-5768
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer-Verlag London L
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Book 2013rformance 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.
发表于 2025-3-23 05:51:09 | 显示全部楼层
https://doi.org/10.1007/978-3-642-94523-6. presents historical review of multiresolution analysis and wavelet transform. Various kinds of wavelet transform applied to signal processing applications viz. continuous wavelet transform (CWT) and DWT (one dimension and two dimensions) are discussed in brief. . reviews implementation issues and
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