Optimized Shape Adaptive Wavelets with Reduced Computational Cost

A. Mertins; K. N. Ngan

Optimized Shape Adaptive Wavelets with Reduced Computational Cost

Institute of Signal Processing

University of Western Australia

Abstract

Wavelets are often characterized through their number of vanishing moments. The more vanishing moments a wavelet has the better are the compaction properties for low-order polynomial signals. However, when bounding wavelets on intervals in order to define wavelet transforms over regions of arbitrary support, some of the moment properties get lost. This is typically accompanied with a loss of compaction gain and other unwanted effects. In this paper, we present methods for recovering the moment properties in the boundary regions. The approach recovers the moments step by step, requires a low number of computations and is well suited for the implementation with finite-precision arithmetic.

Original language	English
Pages	616-620
Number of pages	5
Publication status	Published - 01.11.1998
Event	Proc. IEEE Int. Workshop on Intelligent Signal Processing and Communication Systems 1998 - Melbourne, Australia Duration: 04.11.1998 → 06.11.1998

Conference

Conference	Proc. IEEE Int. Workshop on Intelligent Signal Processing and Communication Systems 1998
Abbreviated title	ISPACS 98
Country/Territory	Australia
City	Melbourne
Period	04.11.98 → 06.11.98

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Cite this

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title = "Optimized Shape Adaptive Wavelets with Reduced Computational Cost",

abstract = "Wavelets are often characterized through their number of vanishing moments. The more vanishing moments a wavelet has the better are the compaction properties for low-order polynomial signals. However, when bounding wavelets on intervals in order to define wavelet transforms over regions of arbitrary support, some of the moment properties get lost. This is typically accompanied with a loss of compaction gain and other unwanted effects. In this paper, we present methods for recovering the moment properties in the boundary regions. The approach recovers the moments step by step, requires a low number of computations and is well suited for the implementation with finite-precision arithmetic.",

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year = "1998",

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T1 - Optimized Shape Adaptive Wavelets with Reduced Computational Cost

AU - Mertins, A.

AU - Ngan, K. N.

PY - 1998/11/1

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N2 - Wavelets are often characterized through their number of vanishing moments. The more vanishing moments a wavelet has the better are the compaction properties for low-order polynomial signals. However, when bounding wavelets on intervals in order to define wavelet transforms over regions of arbitrary support, some of the moment properties get lost. This is typically accompanied with a loss of compaction gain and other unwanted effects. In this paper, we present methods for recovering the moment properties in the boundary regions. The approach recovers the moments step by step, requires a low number of computations and is well suited for the implementation with finite-precision arithmetic.

AB - Wavelets are often characterized through their number of vanishing moments. The more vanishing moments a wavelet has the better are the compaction properties for low-order polynomial signals. However, when bounding wavelets on intervals in order to define wavelet transforms over regions of arbitrary support, some of the moment properties get lost. This is typically accompanied with a loss of compaction gain and other unwanted effects. In this paper, we present methods for recovering the moment properties in the boundary regions. The approach recovers the moments step by step, requires a low number of computations and is well suited for the implementation with finite-precision arithmetic.

UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.32.7086

UR - https://www.researchgate.net/publication/2441611_Optimized_Shape_Adaptive_Wavelets_With_Reduced_Computational_Cost

M3 - Conference Papers

SP - 616

EP - 620

T2 - Proc. IEEE Int. Workshop on Intelligent Signal Processing and Communication Systems 1998

Y2 - 4 November 1998 through 6 November 1998

ER -

Optimized Shape Adaptive Wavelets with Reduced Computational Cost

Abstract

Conference

UN SDGs

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