Paper
22 October 1993 Efficient signal extension for subband/wavelet decomposition of arbitrary-length signals
Herjan J. Barnard, Jos H. Weber, Jan Biemond
Author Affiliations +
Proceedings Volume 2094, Visual Communications and Image Processing '93; (1993) https://doi.org/10.1117/12.158013
Event: Visual Communications and Image Processing '93, 1993, Cambridge, MA, United States
Abstract
Compression of digital signals is often performed with a two-band subband/wavelet decomposition scheme. Conventional tree-structured schemes with depth k that are based on this two-channel scheme require an input signal of which the length is a multiple of 2k. Normally, if the input signal does not meet this condition, samples are added to it until the requirement is met. However, these extra samples lead to an increase in data. In this paper a new method is presented that is based on an efficient way of signal extension. With this method, signals of arbitrary length N can be decomposed into subbands up to arbitrary level without an increase in data. Furthermore, a new alternative boundary extension method for filtering even length signals with symmetric odd length filters is presented. This so-called symmetric-periodic extension is closely related to the new efficient signal extension method and has the advantage of having periodicity 2N. In this paper all signal extensions are explained visually with diagrams to clearly demonstrate perfect reconstruction conditions.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Herjan J. Barnard, Jos H. Weber, and Jan Biemond "Efficient signal extension for subband/wavelet decomposition of arbitrary-length signals", Proc. SPIE 2094, Visual Communications and Image Processing '93, (22 October 1993); https://doi.org/10.1117/12.158013
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Cited by 25 scholarly publications and 1 patent.
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KEYWORDS
Electronic filtering

Visualization

Discrete wavelet transforms

Image compression

Receivers

Linear filtering

Transform theory

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