Scalable One-dimensional Discrete Wavelet Filter Design Using Data Reordering 


Vol. 27,  No. 11, pp. 1040-1046, Nov.  2002


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  Abstract

In this paper, we design a scalable one-dimensional discrete wavelet filter using data reordering. At each level,the required hardware is optimized by sharing multipliers and adders because the input rate is reduced by a factor of two at each level due to decimation. The proposed architecture shows 100% hardware utilization by balancing the hardware with input rate. Furthermore, sharing the coefficients of the high-pass and the low-pass filters using the mirror filter property reduces the number of multipliers and adders in half. We designed a regular data reordering structure that reorders and feeds inputs to high and low pass filters efficiently. The proposed data reordering based architecture is quite reqular to implement in VLSI and can be easily extended to an arbitrary ID DWT structure with M taps and J levels. Compared with other architectures, the proposed discrete wavelet filter shows efficiency in performance with relatively less hardware.

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  Cite this article

[IEEE Style]

T. Park and C. Song, "Scalable One-dimensional Discrete Wavelet Filter Design Using Data Reordering," The Journal of Korean Institute of Communications and Information Sciences, vol. 27, no. 11, pp. 1040-1046, 2002. DOI: .

[ACM Style]

Tae-geun Park and Chang-joo Song. 2002. Scalable One-dimensional Discrete Wavelet Filter Design Using Data Reordering. The Journal of Korean Institute of Communications and Information Sciences, 27, 11, (2002), 1040-1046. DOI: .

[KICS Style]

Tae-geun Park and Chang-joo Song, "Scalable One-dimensional Discrete Wavelet Filter Design Using Data Reordering," The Journal of Korean Institute of Communications and Information Sciences, vol. 27, no. 11, pp. 1040-1046, 11. 2002.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880