Wavelet Folding and Decorrelation Across the Scale

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Title: Wavelet Folding and Decorrelation Across the Scale
Author: Baraniuk, Richard G.; Wells, R.O.; Tian, Jun Feng
Type: Conference Paper
Citation: R. G. Baraniuk, R. Wells and J. F. Tian,"Wavelet Folding and Decorrelation Across the Scale," in IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP),, pp. 544-547.
Abstract: The discrete wavelet transform (DWT) gives a compact multiscale representation of signals and provides a hierarchical structure for signal processing. It has been assumed the DWT can fairly well decorrelate real-world signals. However a residual dependency structure still remains between wavelet coefficients. It has been observed magnitudes of wavelet coefficients are highly correlated, both across the scale and at neighboring spatial locations. In this paper we present a wavelet folding technique, which folds wavelet coefficients across the scale and removes the across-the-scale dependence to a larger extent. It produces an even more compact signal representation and the energy is more concentrated in a few large coefficients. It has a great potential in applications such as image compression.
Date Published: 2000-06-01

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    Publications by Rice University Electrical and Computer Engineering faculty and graduate students
  • DSP Publications [508 items]
    Publications by Rice Faculty and graduate students in digital signal processing.