• MALSORI
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• no.66
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• pp.73-86
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• 2008

Beamforming is one of the spatial filtering techniques which extract only desired signals from noisy environments using microphone arrays. Fixed beamforming is a simple concept and easy to implement. However, it does not show good performance in real noisy conditions. As an adaptive beamforming, Frost algorithm can be a good candidate. It uses the concept of the linearly constrained minimum variance (LCMV) algorithm. The difference between the Frost and the LCMV algorithm is the error correction scheme which is very effective feature in the aspect of performance. In this paper, as quadrature mirror filtering (QMF)-based filterbank is utilized as the pre-processing of the Frost beamformning, the filter length and the learning rate of each band is optimized to improve the performance. The performance is measured by the signal-to-noise ratio (SNR) and the Bark's scale spectral distortion (BSD).

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.677-680
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• 1998

In this paper, we proposed a lwo bit rate subband coding with adaptive vector quantization using the correlation between motion vector and block energy in subband. In this method, the difference between the input signal and the motion compensated interframe prediction signal is decomposed into several narrow bands using quadrature mirror filter (QMF) structure. The subband signals are then quantized by adaptive vector quantizers. In the codebook generating process, each classified region closer to the block value in the same region after the classification of region by the magnitude of motion vector and the variance values of subband block. Because codebook is genrated considering energy distribution of each region classified by motion vector and variance of subband block, this technique gives a very good visual quality at low bit rate coding.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.4
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• pp.1072-1086
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• 1998

Transform, subband, and wavelet transform decompositions are powerful linear transformation tools in image coding because of their decorrelating effects on image pixels, the concentration of energy in a few coefficients, their multirat/multiresolution framework, and their frequency splitting, which allows for efficient coding matched to the statistics of each frequency band and to the characteristics of the human visulal system. Thus, a growingbody of research has bee performed to extend these tools in various kinds of modified formations. Hence, in this paper, an overall survey to achieve a general view on these transformation tools have been attempted. Starting from basic tools such as orthogonal transforms, lapped transforms, QMF(quadrature mirror filter) subband filter banks, and wavelet transforms, their hierarchical extensions, vector extensions, and linear time-varying extensions are investugated in detail.