Efficient Algorithms for Discrete Wavelet Transform (Record no. 54729)
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fixed length control field | 04058nam a22005415i 4500 |
001 - CONTROL NUMBER | |
control field | 978-1-4471-4941-5 |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20200421111656.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 130125s2013 xxk| s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
ISBN | 9781447149415 |
-- | 978-1-4471-4941-5 |
082 04 - CLASSIFICATION NUMBER | |
Call Number | 006.6 |
082 04 - CLASSIFICATION NUMBER | |
Call Number | 006.37 |
100 1# - AUTHOR NAME | |
Author | Shukla, K. K. |
245 10 - TITLE STATEMENT | |
Title | Efficient Algorithms for Discrete Wavelet Transform |
Sub Title | With Applications to Denoising and Fuzzy Inference Systems / |
300 ## - PHYSICAL DESCRIPTION | |
Number of Pages | IX, 91 p. 46 illus., 31 illus. in color. |
490 1# - SERIES STATEMENT | |
Series statement | SpringerBriefs in Computer Science, |
505 0# - FORMATTED CONTENTS NOTE | |
Remark 2 | Introduction -- Filter Banks and DWT -- Finite Precision Error Modeling and Analysis -- PVM Implementation of DWT-Based Image Denoising -- DWT-Based Power Quality Classification -- Conclusions and Future Directions. |
520 ## - SUMMARY, ETC. | |
Summary, etc | Transforms are an important part of an engineer's toolkit for solving signal processing and polynomial computation problems. In contrast to the Fourier transform-based approaches where a fixed window is used uniformly for a range of frequencies, the wavelet transform uses short windows at high frequencies and long windows at low frequencies. This way, the characteristics of non-stationary disturbances can be more closely monitored. In other words, both time and frequency information can be obtained by wavelet transform. Instead of transforming a pure time description into a pure frequency description, the wavelet transform finds a good promise in a time-frequency description. Due to its inherent time-scale locality characteristics, the discrete wavelet transform (DWT) has received considerable attention in digital signal processing (speech and image processing), communication, computer science and mathematics. Wavelet transforms are known to have excellent energy compaction characteristics and are able to provide perfect reconstruction. Therefore, they are ideal for signal/image processing. The shifting (or translation) and scaling (or dilation) are unique to wavelets. Orthogonality of wavelets with respect to dilations leads to multigrid representation. The nature of wavelet computation forces us to carefully examine the implementation methodologies. 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 requirement, storage requirement, and with better signal-to-noise ratio in the reconstructed signal. |
700 1# - AUTHOR 2 | |
Author 2 | Tiwari, Arvind K. |
856 40 - ELECTRONIC LOCATION AND ACCESS | |
Uniform Resource Identifier | http://dx.doi.org/10.1007/978-1-4471-4941-5 |
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Koha item type | eBooks |
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-- | Springer London : |
-- | Imprint: Springer, |
-- | 2013. |
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-- | computer |
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-- | online resource |
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-- | text file |
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650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Computer science. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Algorithms. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Image processing. |
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Computer Science. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Image Processing and Computer Vision. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Signal, Image and Speech Processing. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Algorithm Analysis and Problem Complexity. |
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-- | 2191-5768 |
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