Title :
Reducing the effects of quantization error in image compression systems: estimation of wavelet reconstruction filters using the LMS algorithm
Author :
Prager, Kenneth E. ; Singer, Paul F.
Author_Institution :
Hughes Aircraft Co., El Segundo, CA, USA
Abstract :
The results of an investigation into the use of the least mean square (LMS) algorithm as a tool for the estimating the proper reconstruction filters in a wavelet-based compression system are reported. The LMS algorithm is used to determine the inverse model of the process responsible for creating the correlated noise. The LMS coefficients describing this inverse model can be stored along with the compressed data. Upon reconstruction, these coefficients can be preconvolved with the wavelet filter pair, g(n) and h(n), creating a new filter pair, g´(n ) and h´(n). When this new filter pair is used to reconstruct the compressed signal, the effects of distortions are reduced
Keywords :
analogue-digital conversion; data compression; filtering and prediction theory; image coding; least squares approximations; wavelet transforms; LMS algorithm; LMS coefficients; correlated noise; distortion reduction; image coding; image compression systems; inverse model; least mean square; quantization error; subband coding; wavelet reconstruction filters; Aircraft; Distortion; Filters; Image coding; Image reconstruction; Inverse problems; Least squares approximation; Multiresolution analysis; Quantization; Wavelet analysis;
Conference_Titel :
Time-Frequency and Time-Scale Analysis, 1992., Proceedings of the IEEE-SP International Symposium
Conference_Location :
Victoria, BC
Print_ISBN :
0-7803-0805-0
DOI :
10.1109/TFTSA.1992.274154
