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Efficient Algorithms for Discrete Wavelet Transform By K K Shukla

Efficient Algorithms for Discrete Wavelet Transform by K K Shukla

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Summary

Due to its inherent time-scale locality characteristics, the discrete wavelet transform (DWT) has received considerable attention in signal/image processing. 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.

Efficient Algorithms for Discrete Wavelet Transform Summary

Efficient Algorithms for Discrete Wavelet Transform: With Applications to Denoising and Fuzzy Inference Systems by K K Shukla

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.

Table of Contents

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

Additional information

NLS9781447149408
9781447149408
1447149408
Efficient Algorithms for Discrete Wavelet Transform: With Applications to Denoising and Fuzzy Inference Systems by K K Shukla
New
Paperback
Springer London Ltd
2013-02-07
91
N/A
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