Title :
Optimal quantization in non-orthogonal subband coders
Author :
Gandhi, Rajeev ; Mitra, Sanjit K.
Author_Institution :
Dept. of Electr. & Comput. Eng., California Univ., Santa Barbara, CA, USA
Abstract :
It is well known that the mean square error (MSE) is not preserved under non-orthogonal transformations. This poses a significant challenge to quantize the subband signals in coders that involve non-orthogonal filter banks, since the nearest neighbor (NN) encoding rule can no longer be applied to quantize the coefficients. In this paper, we develop techniques for optimal quantization of the subband coefficients in non-orthogonal subband coders. An exhaustive-search based quantization approach is proposed. The complexity of this approach is shown to increase exponentially with the length of the signal. Next, a reduced complexity solution in the form of a trellis-based search is proposed. Simulation results indicate appreciable SNR gains over standard coding techniques for non-orthogonal filter banks.
Keywords :
channel bank filters; computational complexity; encoding; filtering theory; mean square error methods; optimisation; quantisation (signal); search problems; MSE; SNR; exhaustive-search based quantization; image compression; mean square error; nearest neighbor encoding rule; nonorthogonal filter banks; nonorthogonal subband coders; nonorthogonal transformations; optimal quantization; reduced complexity solution; signal length; simulation results; subband coefficients; subband signal quantization; trellis-based quantization; trellis-based search; Channel bank filters; Ear; Entropy coding; Filter bank; Image coding; Image reconstruction; Mean square error methods; Neural networks; Quantization; Signal synthesis;
Conference_Titel :
Signals, Systems, and Computers, 1999. Conference Record of the Thirty-Third Asilomar Conference on
Conference_Location :
Pacific Grove, CA, USA
Print_ISBN :
0-7803-5700-0
DOI :
10.1109/ACSSC.1999.831895
