TY - GEN
T1 - Noisy signal compression based on optimal search in wavelet bintree
AU - Zhang, Lei
AU - Bao, Paul
N1 - Publisher Copyright:
© 2002 IEEE.
PY - 2002/7
Y1 - 2002/7
N2 - This paper presents a wavelet based simultaneous de-noising and compression scheme for noisy signal. The orthogonal wavelet transform (OWT), used in the traditional signal coding and denoising, is translation variant, which hinders its performance in the signal processing. It is also interesting if an optimal waveform can be selected from a family of wavelet bases to best transform a set of functions for the efficient compression. In this paper the wavelet bintree decomposition (WBD), a translation invariant transform, is proposed and an optimal family of wavelet bases is selected. The bases better de-correlate the input signal than the OWT and represent the signal compactly. Wavelet thresholding is then applied on wavelet coefficients for denoising. Thresholding is similar to the quantizing of a zero- zone in lossy encoding procedure, in this paper a signal adaptive nearly optimal threshold is computed for denoising and the wavelet coefficients after the thresholding are quantized for compression. Experiments show that the presented encoding scheme outperforms the OWT-based method.
AB - This paper presents a wavelet based simultaneous de-noising and compression scheme for noisy signal. The orthogonal wavelet transform (OWT), used in the traditional signal coding and denoising, is translation variant, which hinders its performance in the signal processing. It is also interesting if an optimal waveform can be selected from a family of wavelet bases to best transform a set of functions for the efficient compression. In this paper the wavelet bintree decomposition (WBD), a translation invariant transform, is proposed and an optimal family of wavelet bases is selected. The bases better de-correlate the input signal than the OWT and represent the signal compactly. Wavelet thresholding is then applied on wavelet coefficients for denoising. Thresholding is similar to the quantizing of a zero- zone in lossy encoding procedure, in this paper a signal adaptive nearly optimal threshold is computed for denoising and the wavelet coefficients after the thresholding are quantized for compression. Experiments show that the presented encoding scheme outperforms the OWT-based method.
UR - https://www.scopus.com/pages/publications/84948654212
U2 - 10.1109/ICDSP.2002.1028140
DO - 10.1109/ICDSP.2002.1028140
M3 - Conference article published in proceeding or book
AN - SCOPUS:84948654212
T3 - International Conference on Digital Signal Processing, DSP
SP - 513
EP - 516
BT - 2002 14th International Conference on Digital Signal Processing Proceedings, DSP 2002
A2 - Skodras, A.N.
A2 - Constantinides, A.G.
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th International Conference on Digital Signal Processing, DSP 2002
Y2 - 1 July 2002 through 3 July 2002
ER -